| Status | Citation (Found) | Matched Data / Notes | Actions |
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Autopsy & forensics Amita, R.; Arunkumar, P.; Avedschmidt, S.; Banerjee, P.; French, K.; Ghandili, M. (2021) |
Raw: Amita, R., Arunkumar, P., Avedschmidt, S., Banerjee, P., French, K., Ghandili, M. (2021). Autopsy & forensics. https://www.pathologyoutlines.com/autopsy.html
The citation references a non-existent URL and attributes authorship to a list of individuals that does not align with PathologyOutlines contributor records. The citation is a hallucination.
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Not Found
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TF-IDF explained and Python Sklearn implementation Borcan, M. (2020) |
Raw: Borcan, M. (2020). TF-IDF explained and Python Sklearn implementation. https://towardsdatascience.com/tf-idf-explained-and-python-sklearn-implementation-b020c5e83275
The article is hosted on the Medium platform under the Towards Data Science publication. The author and title are correctly identified. Cited URL is unreachable (https://towardsdatascience.com/tf-idf-explained-and-python-sklearn-implementation-b020c5e83275); no independent live source was confirmed — not_found.
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The Czech Court Decisions Corpus (CzCDC): Availability as the First Step Novotn a, T.; Harasta, J. (2019) arXiv |
Raw: Novotn a, T., & Harasta, J. (2019). The Czech Court Decisions Corpus (CzCDC): Availability as the First Step. arXiv preprint arXiv:1910.09513.
Match: The Czech Court Decisions Corpus (CzCDC): Availability as the First Step
Venue: arXiv DOI: 10.48550/arXiv.1910.09513 ISBN: URL: https://arxiv.org/abs/1910.09513
CrossRef arxiv_static matches title/DOI (score: 1.00), but cited author identities disagree with the official list. Unmatched cited author(s): Novotn a, T.. Official authors: Tereza Novotná, Jakub Harašta.
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Integrating topic modeling and word embedding to characterize violent deaths Arseniev-Koehler, A.; Cochran, S. D.; Mays, V. M.; Chang, K.-W.; Foster, J. G. (2022) Proceedings of the National Academy of Sciences |
Raw: Arseniev-Koehler, A., Cochran, S. D., Mays, V. M., Chang, K.- W., & Foster, J. G. (2022). Integrating topic modeling and word embedding to characterize violent deaths. Proceedings of the National Academy of Sciences, 119(10), e2108801119. https://doi.org/10.1073/pnas.2108801119
Match: Integrating topic modeling and word embedding to characterize violent deaths
Venue: Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.2108801119 ISBN: URL: https://doi.org/10.1073/pnas.2108801119
Verified via static CrossRef title search (score: 0.96)
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Individual vs. group violent threats classification in online discussions Ashraf, N.; Mustafa, R.; Sidorov, G.; Gelbukh, A. (2020) 29th World Wide Web Conference (WWW) |
Raw: Ashraf, N., Mustafa, R., Sidorov, G., & Gelbukh, A. (2020) Individual vs. group violent threats classification in online discussions [Paper presentation]. 29th World Wide Web Conference (WWW) (pp. 629-633), Taipei, Taiwan. https://doi.org/10.1145/3366424.3385778
The cited venue is acceptable as the Companion Proceedings are part of the main WWW conference.
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Smart policing technique with crime type and risk score prediction based on machine learning for early awareness of risk situation Baek, M. S.; Park, W.; Park, J.; Jang, K. H.; Lee, Y. T. (2021) IEEE Access |
Raw: Baek, M. S., Park, W., Park, J., Jang, K. H., & Lee, Y. T. (2021). Smart policing technique with crime type and risk score prediction based on machine learning for early awareness of risk situation. IEEE Access, 9, 131906- 131915. https://doi.org/10.1109/ACCESS.2021.3112682
Match: Smart Policing Technique With Crime Type and Risk Score Prediction Based on Machine Learning for Early Awareness of Risk Situation
Venue: IEEE Access DOI: 10.1109/access.2021.3112682 ISBN: URL: https://doi.org/10.1109/access.2021.3112682
Verified via static CrossRef title search (score: 1.00)
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Conceptualizing self-regulated reading-to-write in ESL/EFL writing and investigating its relationships to motivation and writing competence Bai, B.; Wang, J. (2023) Language Teaching Research |
Raw: Bai, B., & Wang, J. (2023). Conceptualizing self-regulated reading-to-write in ESL/EFL writing and investigating its relationships to motivation and writing competence. Language Teaching Research, 27(5), 1193-1216. https:// doi.org/10.1177/1362168820971740
The space in the DOI URL is a minor formatting artifact; the work and all bibliographic details are correct.
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Unsupervised identification of crime problems from police free-text data Birks, D.; Coleman, A.; Jackson, D. (2020) Crime Science |
Raw: Birks, D., Coleman, A., & Jackson, D. (2020). Unsupervised identification of crime problems from police free-text data. Crime Science, 9(1), 18. https://doi.org/10.1186/s40163-020-00127-4
Match: Unsupervised identification of crime problems from police free-text data
Venue: Crime Science DOI: 10.1186/s40163-020-00127-4 ISBN: URL: https://doi.org/10.1186/s40163-020-00127-4
Verified via static CrossRef title search (score: 1.00)
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Homicides by sharp force Bohnert, M.; Huttemann, H.; Schmidt, U. (2006) Humana Press |
Raw: Bohnert, M., Huttemann, H., & Schmidt, U. (2006). € Homicides by sharp force. In M. Tsokos (Ed.), Forensic pathology reviews (Vol. 4, pp. 65-89). Humana Press.
Extraneous '€' symbol in title confirmed as an OCR/encoding artifact.
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An annotated corpus of crime-related Portuguese documents for NLP and machine learning processing Carnaz, G.; Antunes, M.; Nogueira, V. B. (2021) Data |
Raw: Carnaz, G., Antunes, M., & Nogueira, V. B. (2021). An annotated corpus of crime-related Portuguese documents for NLP and machine learning processing. Data, 6(7), 71. https://doi.org/10.3390/data6070071
Match: An Annotated Corpus of Crime-Related Portuguese Documents for NLP and Machine Learning Processing
Venue: Data DOI: 10.3390/data6070071 ISBN: URL: https://doi.org/10.3390/data6070071
Verified via static CrossRef title search (score: 1.00)
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The LATO knowledge model for automated knowledge extraction and enrichment from court decisions corpora Castano, S.; Falduti, M.; Ferrara, A.; Montanelli, S. (2020) First International Workshop "CAiSE for Legal Documents" |
Raw: Castano, S., Falduti, M., Ferrara, A., & Montanelli, S. (2020). The LATO knowledge model for automated knowledge extraction and enrichment from court decisions corpora [Paper presentation]. First International Workshop "CAiSE for Legal Documents", co-Located with the 32nd International Conference on Advanced Information Systems Engineering, CAiSE (2020) (Vol. 2690, pp. 15- 26), Grenoble, France.
Work identified in CEUR Workshop Proceedings, Vol. 2690, COUrT 2020.
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Mining the Harvard Caselaw Access Project Chang, F.; McCabe, E.; Lee, J. (2020) SSRN |
Raw: Chang, F., McCabe, E., & Lee, J. (2020). Mining the Harvard Caselaw Access Project. Available at SSRN 3529257.
Match: Mining the Harvard Caselaw Access Project
Venue: SSRN Electronic Journal DOI: 10.2139/ssrn.3529257 ISBN: URL: https://doi.org/10.2139/ssrn.3529257
Verified via static CrossRef title search (score: 0.99)
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Brazilian court documents clustered by similarity together using natural language processing approaches with transformers De Oliveira, R. S.; Nascimento, E. G. S. (2022) arXiv |
Raw: De Oliveira, R. S., & Nascimento, E. G. S. (2022). Brazilian court documents clustered by similarity together using natural language processing approaches with transformers. arXiv Preprint, arXiv 220407182.
Match: Brazilian Court Documents Clustered by Similarity Together Using Natural Language Processing Approaches with Transformers
Venue: arXiv DOI: 10.48550/arXiv.2204.07182 ISBN: URL: https://arxiv.org/abs/2204.07182
Verified against the arXiv repository.
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Automatic curation of court documents: Anonymizing personal data Garat, D.; Wonsever, D. (2022) Information |
Raw: Garat, D., & Wonsever, D. (2022). Automatic curation of court documents: Anonymizing personal data. Information, 13(1), 27. https://doi.org/10.3390/info13010027
Match: Automatic Curation of Court Documents: Anonymizing Personal Data
Venue: Information DOI: 10.3390/info13010027 ISBN: URL: https://doi.org/10.3390/info13010027
Verified via static CrossRef title search (score: 1.00)
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Assessing the risk of repeat victimization using structured and unstructured police information Geurts, R.; Raaijmakers, N.; Delsing, M. J. M. H.; Spapens, T.; Wientjes, J.; Willems, D.; Scholte, R. H. J. (2023) Crime & Delinquency |
Raw: Geurts, R., Raaijmakers, N., Delsing, M. J. M. H., Spapens, T., Wientjes, J., Willems, D., & Scholte, R. H. J. (2023). Assessing the risk of repeat victimization using structured and unstructured police information. Crime & Delinquency, 69(9), 1736-1757. https://doi.org/10.1177/00111287211047533
The citation provided is accurate and corresponds to the official publication record.
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Writing to read: Evidence for how writing can improve reading: A report from Carnegie Corporation of New York Graham, S.; Hebert, M. (2010) Carnegie Corporation of New York |
Raw: Graham, S., & Hebert, M. (2010). Writing to read: Evidence for how writing can improve reading: A report from Carnegie Corporation of New York.
Verified as a 2010 Carnegie Corporation Time to Act report.
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A two-staged NLP-based framework for assessing the sentiments on Indian supreme court judgments Gupta, I.; Chatterjee, I.; Gupta, N. (2023) International Journal of Information Technology |
Raw: Gupta, I., Chatterjee, I., & Gupta, N. (2023). A two-staged NLP-based framework for assessing the sentiments on Indian supreme court judgments. International Journal of Information Technology, 15(4), 2273-2282. https://doi.org/10.1007/s41870-023-01273-z
Match: A two-staged NLP-based framework for assessing the sentiments on Indian supreme court judgments
Venue: International Journal of Information Technology DOI: 10.1007/s41870-023-01273-z ISBN: URL: https://doi.org/10.1007/s41870-023-01273-z
Verified via static CrossRef title search (score: 1.00)
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Mining legal arguments in court decisions Habernal, I.; Faber, D.; Recchia, N.; Bretthauer, S.; Gurevych, I.; Spiecker Genannt Dohmann, I.; Burchard, C. (2023) Artificial Intelligence and Law |
Raw: Habernal, I., Faber, D., Recchia, N., Bretthauer, S., Gurevych, I., Spiecker Genannt Dohmann, I., & Burchard, C. (2023). € Mining legal arguments in court decisions. Artificial Intelligence and Law,1-38. https://doi.org/10.1007/s10506-023-09361-y
Match: Mining legal arguments in court decisions
Venue: Artificial Intelligence and Law DOI: 10.1007/s10506-023-09361-y ISBN: URL: https://doi.org/10.1007/s10506-023-09361-y
Verified via static CrossRef title search (score: 1.00)
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HeinOnline databases - Case law HeinOnline (2022) |
Raw: HeinOnline. (2022). HeinOnline databases - Case law. https://home.heinonline.org/content/case-law/
Match: HeinOnline databases - Case law
Venue: HeinOnline DOI: ISBN: URL: https://home.heinonline.org/content/case-law/
The citation points to a valid, live landing page for HeinOnline's case law resources.
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A quick guide to text cleaning using the nltk library Joshi, Y. (2020) |
Raw: Joshi, Y. (2020). A quick guide to text cleaning using the nltk library. https://www.analyticsvidhya.com/blog/2020/11/text-cleaning-nltk-library/#h2_2
Article identified on Analytics Vidhya. The author matches the cited name.
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Surveillance of domestic violence using text mining outputs from Australian police records Karystianis, G.; Adily, A.; Schofield, P. W.; Wand, H.; Lukmanjaya, W.; Buchan, I.; Nenadic, G.; Butler, T. (2022) Frontiers in Psychiatry |
Raw: Karystianis, G., Adily, A., Schofield, P. W., Wand, H., Lukmanjaya, W., Buchan, I., Nenadic, G., & Butler, T. (2022). Surveillance of domestic violence using text mining outputs from Australian police records. Frontiers in Psychiatry, 12, 787792. https://doi.org/10.3389/fpsyt.2021.787792
Match: Surveillance of Domestic Violence Using Text Mining Outputs From Australian Police Records
Venue: Frontiers in Psychiatry DOI: 10.3389/fpsyt.2021.787792 ISBN: URL: https://doi.org/10.3389/fpsyt.2021.787792
Verified via static CrossRef title search (score: 1.00)
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Research paper classification systems based on TF-IDF and LDA schemes Kim, S.-W.; Gil, J.-M. (2019) HumanCentric Computing and Information Sciences |
Raw: Kim, S.-W., & Gil, J.-M. (2019). Research paper classification systems based on TF-IDF and LDA schemes. HumanCentric Computing and Information Sciences, 9(1), 30. https://doi.org/10.1186/s13673-019-0192-7
Match: Research paper classification systems based on TF-IDF and LDA schemes
Venue: Human-centric Computing and Information Sciences DOI: 10.1186/s13673-019-0192-7 ISBN: URL: https://doi.org/10.1186/s13673-019-0192-7
Verified via static CrossRef title search (score: 1.00)
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Activity, context, and plan recognition with computational causal behaviour models Kruger, F. (2016) |
Raw: Kruger, F. (2016). € Activity, context, and plan recognition with computational causal behaviour models [PhD Thesis]. Computer Science and Electrical Engineering, Rostock University.
Verified against the University of Rostock's official repository (RosDok). Spelling difference in name (Kruger vs. Krüger) is minor.
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Crime topic modeling Kuang, D.; Brantingham, P. J.; Bertozzi, A. L. (2017) Crime Science |
Raw: Kuang, D., Brantingham, P. J., & Bertozzi, A. L. (2017). Crime topic modeling. Crime Science, 6(1), 12. https:// doi.org/10.1186/s40163-017-0074-0
Match: Crime topic modeling
Venue: Crime Science DOI: 10.1186/s40163-017-0074-0 ISBN: URL: https://doi.org/10.1186/s40163-017-0074-0
Verified via static CrossRef title search (score: 1.00)
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Predicting Brazilian court decisions Lage-Freitas, A.; Allende-Cid, H.; Santana, O.; de OliveiraLage, L. (2022) Peer Journal of Computer Science |
Raw: Lage-Freitas, A., Allende-Cid, H., Santana, O., & de OliveiraLage, L. (2022). Predicting Brazilian court decisions. Peer Journal of Computer Science, 8, e904. https://doi.org/10. 7717/peerj-cs.904
Match: Predicting Brazilian Court Decisions
Venue: PeerJ Computer Science DOI: 10.7717/peerj-cs.904 ISBN: URL: https://doi.org/10.7717/peerj-cs.904
Verified via static CrossRef title search (score: 1.00)
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Analysis and classification of crime tweets Lal, S.; Tiwari, L.; Ranjan, R.; Verma, A.; Sardana, N.; Mourya, R. (2020) |
Raw: Lal, S., Tiwari, L., Ranjan, R., Verma, A., Sardana, N., & Mourya, R. (2020). Analysis and classification of crime tweets. In International conference on computational intelligence and data science (ICCIDS) (vol. 167, pp. 1911- 1919). NorthCap University.
Verified; conference proceedings citation for Procedia Computer Science volume is standard and correct.
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An approach for understanding offender modus operandi to detect serial robbery crimes Li, Y.-S.; Qi, M.-L. (2019) Journal of Computational Science |
Raw: Li, Y.-S., & Qi, M.-L. (2019). An approach for understanding offender modus operandi to detect serial robbery crimes. Journal of Computational Science, 36, 101024. https://doi.org/10.1016/j.jocs.2019.101024
Match: An approach for understanding offender modus operandi to detect serial robbery crimes
Venue: Journal of Computational Science DOI: 10.1016/j.jocs.2019.101024 ISBN: URL: https://doi.org/10.1016/j.jocs.2019.101024
Verified via static CrossRef title search (score: 1.00)
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Measuring similarity among legal court case documents Mandal, A.; Chaki, R.; Saha, S.; Ghosh, K.; Pal, A.; Ghosh, S. (2017) |
Raw: Mandal, A., Chaki, R., Saha, S., Ghosh, K., Pal, A., & Ghosh, S. (2017). Measuring similarity among legal court case documents [Paper presentation]. Proceedings of the 10th Annual ACM India Compute Conference (pp. 1-9), Bhopal, India. https://doi.org/10.1145/3140107.3140119
Match: Measuring Similarity among Legal Court Case Documents
Venue: Proceedings of the 10th Annual ACM India Compute Conference DOI: 10.1145/3140107.3140119 ISBN: URL: https://doi.org/10.1145/3140107.3140119
Verified via static CrossRef title search (score: 1.00)
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Unstructured Malay text analytics model in crime Mohemad, R.; Naziah Mohd Muhait, N.; Maizura Mohamad Noor, N.; Ali Othman, Z. (2020) IOP Conference Series: Materials Science and Engineering |
Raw: Mohemad, R., Naziah Mohd Muhait, N., Maizura Mohamad Noor, N., & Ali Othman, Z. (2020). Unstructured Malay text analytics model in crime. IOP Conference Series: Materials Science and Engineering, 769(1), 012015. https://doi.org/10.1088/1757-899X/769/1/012015
Match: Unstructured Malay Text Analytics Model in Crime
Venue: IOP Conference Series: Materials Science and Engineering DOI: 10.1088/1757-899x/769/1/012015 ISBN: URL: https://doi.org/10.1088/1757-899x/769/1/012015
Verified via static CrossRef title search (score: 1.00)
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Predicting the category and the length of punishment in Indonesian courts based on previous court decision documents Nuranti, E. Q.; Yulianti, E.; Husin, H. S. (2022) Computers |
Raw: Nuranti, E. Q., Yulianti, E., & Husin, H. S. (2022). Predicting the category and the length of punishment in Indonesian courts based on previous court decision documents. Computers, 11(6), 88. https://doi.org/10. 3390/computers11060088
Match: Predicting the Category and the Length of Punishment in Indonesian Courts Based on Previous Court Decision Documents
Venue: Computers DOI: 10.3390/computers11060088 ISBN: URL: https://doi.org/10.3390/computers11060088
Verified via static CrossRef title search (score: 1.00)
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Homicide by stabbing committed with a Fantasy Knife Papi, L.; Gori, F.; Spinetti, I. (2020) Forensic Science International: Reports |
Raw: Papi, L., Gori, F., & Spinetti, I. (2020). Homicide by stabbing committed with a Fantasy Knife. Forensic Science International: Reports, 2, 100068. https://doi.org/10.1016/j.fsir.2020.100068
Match: Homicide by stabbing committed with a "Fantasy Knife"
Venue: Forensic Science International: Reports DOI: 10.1016/j.fsir.2020.100068 ISBN: URL: https://doi.org/10.1016/j.fsir.2020.100068
Verified via static CrossRef title search (score: 1.00)
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Text mining and recommender systems for predictive policing Percy, I.; Balinsky, A.; Balinsky, H.; Simske, S. (2018) |
Raw: Percy, I., Balinsky, A., Balinsky, H., & Simske, S. (2018). Text mining and recommender systems for predictive policing" [Paper presentation]. 18th ACM Symposium on Document Engineering (DocEng), HalifaxCANADA (pp. 1-4). https://doi.org/10.1145/3209280.3229112
Match: Text Mining and Recommender Systems for Predictive Policing
Venue: Proceedings of the ACM Symposium on Document Engineering 2018 DOI: 10.1145/3209280.3229112 ISBN: URL: https://doi.org/10.1145/3209280.3229112
Verified via static CrossRef title search (score: 1.00)
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Extracting outcomes from appellate decisions in US state courts Petrova, A.; Armour, J.; Lukasiewicz, T. (2020) |
Raw: Petrova, A., Armour, J., & Lukasiewicz, T. (2020). Extracting outcomes from appellate decisions in US state courts. Proceedings of the 33rd International Conference on Legal Knowledge and Information Systems, JURIX 2020 (vol. 334, pp. 133-142).
Verified against the JURIX 2020 proceedings, published as Volume 334 in Frontiers in Artificial Intelligence and Applications.
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Effect of hierarchical domain-specific language models and attention in the classification of decisions for legal cases Prasad, N.; Boughanem, M.; Dkaki, T. (2022) |
Raw: Prasad, N., Boughanem, M., & Dkaki, T. (2022). Effect of hierarchical domain-specific language models and attention in the classification of decisions for legal cases [Paper presentation]. Proceedings of the CIRCLE (Joint Conference of the Information Retrieval Communities in Europe) (pp. 4-7), Samatan, Gers, France.
Verified against the proceedings of CIRCLE 2022, published as CEUR-WS Vol-3178.
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The Kalimantan forest fires: An actor analysis based on Supreme Court documents in Indonesia Purnomo, E. P.; Zahra, A. A.; Malawani, A. D.; Anand, P. (2021) Sustainability |
Raw: Purnomo, E. P., Zahra, A. A., Malawani, A. D., & Anand, P. (2021). The Kalimantan forest fires: An actor analysis based on Supreme Court documents in Indonesia. Sustainability, 13(4), 2342. https://doi.org/10.3390/su13042342
Match: The Kalimantan Forest Fires: An Actor Analysis Based on Supreme Court Documents in Indonesia
Venue: Sustainability DOI: 10.3390/su13042342 ISBN: URL: https://doi.org/10.3390/su13042342
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Evaluation of sampling and cross-validation tuning strategies for regional-scale machine learning classification Ramezan, C. A.; Warner, T. A.; Maxwell, A. E. (2019) Remote Sensing |
Raw: Ramezan, C. A., Warner, T. A., & Maxwell, A. E. (2019). Evaluation of sampling and cross-validation tuning strategies for regional-scale machine learning classification. Remote Sensing, 11(2), 185. https://doi.org/10.3390/rs11020185
Match: Evaluation of Sampling and Cross-Validation Tuning Strategies for Regional-Scale Machine Learning Classification
Venue: Remote Sensing DOI: 10.3390/rs11020185 ISBN: URL: https://doi.org/10.3390/rs11020185
Verified via static CrossRef title search (score: 1.00)
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Learning to rank sentences for explaining statutory terms Savelka, J.; Ashley, K. D. (2020) |
Raw: Savelka, J., & Ashley, K. D. (2020). Learning to rank sentences for explaining statutory terms. Proceedings of the 2020 Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL).
Match: Learning to Rank Sentences for Explaining Statutory Terms
Venue: Proceedings of the 2020 Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL), CEUR-WS Vol-2764 DOI: ISBN: URL: https://ceur-ws.org/Vol-2764/paper7.pdf
Verified against the proceedings of the 2020 Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL), published as CEUR-WS Vol-2764.
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Improving sentence retrieval from case law for statutory interpretation Savelka, J.; Xu, H.; Ashley, K. D. (2019) |
Raw: Savelka, J., Xu, H., & Ashley, K. D. (2019). Improving sentence retrieval from case law for statutory interpretation [Paper presentation]. Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law, Montreal, QC, Canada. pp. 113-122. https://doi.org/10.1145/3322640.3326736
Match: Improving Sentence Retrieval from Case Law for Statutory Interpretation
Venue: Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law DOI: 10.1145/3322640.3326736 ISBN: URL: https://doi.org/10.1145/3322640.3326736
Verified via static CrossRef title search (score: 1.00)
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scikit-learn: Machine Learning in Python None (2023) |
Raw: scikit-learn: Machine Learning in Python. (2023). https://sci-kit-learn.org/
The citation references the software project and its official documentation, which is standard practice for this library, rather than the 2011 JMLR paper. Using a recent year for an actively maintained software project is acceptable.
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Supervised classification algorithms in machine learning: A survey and review Sen, P. C.; Hajra, M.; Ghosh, M. (2020) Springer Singapore |
Raw: Sen, P. C., Hajra, M., & Ghosh, M. (2020). Supervised classification algorithms in machine learning: A survey and review. In Emerging technology in modelling and graphics (pp. 99-111). Springer Singapore.
Match: Supervised Classification Algorithms in Machine Learning: A Survey and Review
Venue: Advances in Intelligent Systems and Computing DOI: 10.1007/978-981-13-7403-6_11 ISBN: URL: https://doi.org/10.1007/978-981-13-7403-6_11
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Teaching disciplinary literacy to adolescents: Rethinking content-area literacy Shanahan, T.; Shanahan, C. (2008) Harvard Educational Review |
Raw: Shanahan, T., & Shanahan, C. (2008). Teaching disciplinary literacy to adolescents: Rethinking content-area literacy. Harvard Educational Review, 78(1), 40-59. https://doi.org/10.17763/haer.78.1.v62444321p602101
Match: Teaching Disciplinary Literacy to Adolescents: Rethinking Content- Area Literacy
Venue: Harvard Educational Review DOI: 10.17763/haer.78.1.v62444321p602101 ISBN: URL: https://doi.org/10.17763/haer.78.1.v62444321p602101
Verified via static CrossRef title search (score: 1.00)
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Measuring the antitrust revolution Sokol, D. D.; Bensley, S.; Crook, M. (2020) Antitrust Bulletin |
Raw: Sokol, D. D., Bensley, S., & Crook, M. (2020). Measuring the antitrust revolution. Antitrust Bulletin, 65(4), 499-514. https://doi.org/10.1177/0003603X20950230
Match: Measuring the Antitrust Revolution
Venue: The Antitrust Bulletin DOI: 10.1177/0003603x20950230 ISBN: URL: https://doi.org/10.1177/0003603x20950230
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Multi-label legal document classification: A deep learning-based approach with label-attention and domain-specific pretraining Song, D.; Vold, A.; Madan, K.; Schilder, F. (2022) Information Systems |
Raw: Song, D., Vold, A., Madan, K., & Schilder, F. (2022). Multi-label legal document classification: A deep learning-based approach with label-attention and domain-specific pretraining. Information Systems, 106, 101718. https://doi.org/10.1016/j.is.2021.101718
Match: Multi-label legal document classification: A deep learning-based approach with label-attention and domain-specific pre-training
Venue: Information Systems DOI: 10.1016/j.is.2021.101718 ISBN: URL: https://doi.org/10.1016/j.is.2021.101718
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SALKG: A semantic annotation system for building a high-quality legal knowledge graph Tang, M.; Su, C.; Chen, H.; Qu, J.; Ding, J. (2020) |
Raw: Tang, M., Su, C., Chen, H., Qu, J., & Ding, J. (2020). SALKG: A semantic annotation system for building a high-quality legal knowledge graph [Paper presentation]. 2020 IEEE International Conference on Big Data (Big Data) (pp. 2153-2159), Atlanta, GA, USA. https://doi.org/10.1109/ BigData50022.2020.9378107
Match: SALKG: A Semantic Annotation System for Building a High-quality Legal Knowledge Graph
Venue: 2020 IEEE International Conference on Big Data (Big Data) DOI: 10.1109/bigdata50022.2020.9378107 ISBN: URL: https://doi.org/10.1109/bigdata50022.2020.9378107
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Automated classification of criminal and violent activities in Thailand from online news articles Thaipisutikul, T.; Tuarob, S.; Pongpaichet, S.; Amornvatcharapong, A.; Shih, T. K. (2021) 13th International Conference on Knowledge and Smart Technology (KST) |
Raw: Thaipisutikul, T., Tuarob, S., Pongpaichet, S., Amornvatcharapong, A., & Shih, T. K. (2021). Automated classification of criminal and violent activities in Thailand from online news articles. 13th International Conference on Knowledge and Smart Technology (KST) (pp. 170-175).
Match: Automated Classification of Criminal and Violent Activities in Thailand from Online News Articles
Venue: 2021 13th International Conference on Knowledge and Smart Technology (KST) DOI: 10.1109/kst51265.2021.9415789 ISBN: URL: https://doi.org/10.1109/kst51265.2021.9415789
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The Caselaw Access Project (CAP) None (2022) |
Raw: The Caselaw Access Project (CAP). (2022). https://case.law/about/
The citation refers to the official 'About' page of the Caselaw Access Project. The inclusion of a 2022 retrieval or access date for a dynamic web resource is standard and verified.
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Natural language processing advancements by deep learning: A survey Torfi, A.; Shirvani, R. A.; Keneshloo, Y.; Tavvaf, N.; Fox, E. (2020) arXiv |
Raw: Torfi, A., Shirvani, R. A., Keneshloo, Y., Tavvaf, N., & Fox, E. (2020). Natural language processing advancements by deep learning: A survey. ArXiv, vol. abs/2003.01200.
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Zero-shot transfer of article-aware legal outcome classification for European court of human rights cases Tyss, S.; Ichim, O.; Grabmair, M. (2023) Association for Computational Linguistics |
Raw: Tyss, S., Ichim, O., & Grabmair, M. (2023). Zero-shot transfer of article-aware legal outcome classification for European court of human rights cases. Findings of the association for computational linguistics: EACL 2023 (pp. 593-605). Association for Computational Linguistics.
Match: Zero-shot Transfer of Article-aware Legal Outcome Classification for European Court of Human Rights Cases
Venue: Findings of the Association for Computational Linguistics: EACL 2023 DOI: 10.18653/v1/2023.findings-eacl.44 ISBN: URL: https://doi.org/10.18653/v1/2023.findings-eacl.44
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Classification of US Supreme Court cases using BERT-based techniques Vatsal, S.; Meyers, A.; Ortega, J. (2023) arXiv |
Raw: Vatsal, S., Meyers, A., & Ortega, J. (2023). Classification of US Supreme Court cases using BERT-based techniques. arXiv preprint arXiv:2304.08649.
Match: Classification of US Supreme Court Cases using BERT-Based Techniques
Venue: Proceedings of the Conference Recent Advances in Natural Language Processing - Large Language Models for Natural Language Processings DOI: 10.26615/978-954-452-092-2_128 ISBN: URL: https://doi.org/10.26615/978-954-452-092-2_128
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Automated identification of domestic violence in written child welfare records: Leveraging text mining and machine learning to enhance social work research and evaluation Victor, B. G.; Perron, B. E.; Sokol, R. L.; Fedina, L.; Ryan, J. P. (2021) Journal of the Society for Social Work and Research DOI: 10.1086/712734 |
Raw: Victor, B. G., Perron, B. E., Sokol, R. L., Fedina, L., & Ryan, J. P. (2021). Automated identification of domestic violence in written child welfare records: Leveraging text mining and machine learning to enhance social work research and evaluation. Journal of the Society for Social Work and Research, 12(4), 631-655. https://doi.org/10. 1086/712734
Match: Automated Identification of Domestic Violence in Written Child Welfare Records: Leveraging Text Mining and Machine Learning to Enhance Social Work Research and Evaluation
Venue: Journal of the Society for Social Work and Research DOI: 10.1086/712734 ISBN: URL: https://doi.org/10.1086/712734
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Recreating the scene: An investigation of police report writing Yu, H.; Monas, N. (2020) Journal of Technical Writing and Communication DOI: 10.1177/0047281618812441 |
Raw: Yu, H., & Monas, N. (2020). Recreating the scene: An investigation of police report writing. Journal of Technical Writing and Communication, 50(1), 35-55. https://doi.org/10.1177/0047281618812441
Match: Recreating the Scene: An Investigation of Police Report Writing
Venue: Journal of Technical Writing and Communication DOI: 10.1177/0047281618812441 ISBN: URL: https://doi.org/10.1177/0047281618812441
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Exploration of cross-modal text generation methods in smart justice Zhang, Y. (2021) Scientific Programming |
Raw: Zhang, Y. (2021). Exploration of cross-modal text generation methods in smart justice. Scientific Programming, 2021, 14.
Match: Exploration of Cross-Modal Text Generation Methods in Smart Justice
Venue: Scientific Programming DOI: 10.1155/2021/3225933 ISBN: URL: https://doi.org/10.1155/2021/3225933
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