{"id":"W2262121003","doi":"10.2139/ssrn.2469553","title":"A 19th Century Data Goldmine for Legal Scholars","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Brock University","funders":"","keywords":"Late 19th century; Law; Political science; Art; Aesthetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03984396,0.0004537955,0.001260935,0.004968585,0.01061236,0.01914807,0.003613428,0.0130127,0.01317783],"category_scores_gemma":[0.1118447,0.0007612682,0.0008855985,0.003307123,0.03066211,0.03673191,0.01608518,0.01533529,0.002521014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01030915,"about_ca_system_score_gemma":0.01541231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009419141,"about_ca_topic_score_gemma":0.01130776,"domain_scores_codex":[0.9841457,0.0055739,0.00132911,0.002098791,0.005768758,0.001083822],"domain_scores_gemma":[0.915082,0.04625397,0.002513313,0.01667886,0.01458188,0.00488995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003396827,0.00002176986,0.000542005,0.00005942908,0.000006854699,0.00008560292,0.002962186,0.00009243965,0.0001293841,0.9142756,0.05885626,0.02293439],"study_design_scores_gemma":[0.00002541528,0.00003149044,0.0003127244,0.0004835714,0.000009975734,0.00009905285,0.002571446,0.0005939001,0.0004776196,0.474957,0.5204052,0.0000325456],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.01556427,0.008279656,0.02798968,0.8266213,0.01048788,0.00007811133,0.0006247604,0.0004793522,0.1098751],"genre_scores_gemma":[0.481063,0.008724701,0.06564245,0.2714424,0.0103312,0.000442354,0.0009986415,0.001149678,0.1602057],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03984396,"threshold_uncertainty_score":0.2107175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04575864792703246,"score_gpt":0.3660347236587241,"score_spread":0.3202760757316917,"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."}}