{"id":"W4319877134","doi":"10.29242/lawstats.2021","title":"ARL Academic Law Library Statistics 2021","year":2023,"lang":"en","type":"book","venue":"ARL academic law and medical library statistics","topic":"Legal Education and Practice Innovations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Law library; Library science; Academic library; Law; Political science; Computer science; Statistics; Mathematics","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.002216618,0.001089452,0.0007271268,0.008896505,0.001273718,0.004779859,0.001110562,0.0008909137,0.1249333],"category_scores_gemma":[0.01857389,0.0007537298,0.0004848161,0.0226041,0.0003785258,0.002312014,0.001031765,0.002175627,0.2179854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005873505,"about_ca_system_score_gemma":0.01683666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1945036,"about_ca_topic_score_gemma":0.2111431,"domain_scores_codex":[0.9957621,0.0003027647,0.0002649494,0.0002154042,0.00317185,0.0002829685],"domain_scores_gemma":[0.982967,0.00330451,0.001278535,0.0009679604,0.01071681,0.0007651774],"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":[0.000003423229,0.000002963185,0.0001374558,0.00002184471,7.59114e-7,0.000002185336,0.000006428,0.00003499204,0.000006037603,0.0006265141,0.9906922,0.008465119],"study_design_scores_gemma":[0.000003860921,0.000003745135,0.002337771,0.00009753727,0.000001615441,0.0000140235,0.0000236672,0.000109461,0.00004014352,0.000499098,0.9968601,0.00000901115],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000744411,0.00280753,0.001912813,0.005257962,0.001914796,0.0001974782,0.6827893,0.004794397,0.2995813],"genre_scores_gemma":[0.004714837,0.00498109,0.003961947,0.002806526,0.001329704,0.0004841932,0.5394675,0.002226285,0.4400279],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9911035,"threshold_uncertainty_score":0.4179435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03355264656939061,"score_gpt":0.3517682123872268,"score_spread":0.3182155658178362,"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."}}