{"id":"W2943473700","doi":"","title":"Research Guides: Legal Citation with the 9th edition of the McGill Guide: Neutral Citations","year":2018,"lang":"en","type":"libguides","venue":"","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Citation; Library science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01745331,0.001742774,0.003146066,0.0327478,0.006118163,0.01833184,0.006597687,0.008958497,0.5965629],"category_scores_gemma":[0.1686877,0.002647049,0.001558434,0.04360788,0.003131971,0.01469992,0.004283253,0.006324315,0.5542209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008992803,"about_ca_system_score_gemma":0.04033139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0404847,"about_ca_topic_score_gemma":0.08809327,"domain_scores_codex":[0.973588,0.004975418,0.004056591,0.001452975,0.01454713,0.001379871],"domain_scores_gemma":[0.8204,0.04682368,0.007203219,0.01280154,0.1058376,0.006933918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006459813,0.000008906104,0.00002233611,0.0002063661,0.000001788358,0.000003855763,0.00003620609,0.00001639007,0.00002163047,0.004041889,0.9748296,0.02080465],"study_design_scores_gemma":[0.00001333057,0.00001104239,0.000280608,0.0006725132,0.000005773456,0.00002006954,0.00006439444,0.00007092013,0.0000851635,0.006315147,0.9924355,0.00002554135],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003821532,0.01225968,0.01204142,0.03574878,0.02069432,0.00131251,0.07910685,0.01594027,0.8225142],"genre_scores_gemma":[0.003273757,0.01150908,0.01675609,0.006727032,0.004952048,0.002017942,0.04082592,0.009012006,0.904926],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9816682,"threshold_uncertainty_score":0.5754541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1571471043941266,"score_gpt":0.4430226102223996,"score_spread":0.285875505828273,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}