{"id":"W7019899296","doi":"","title":"Increasing Innovation in Legal Process: The Contribution of Collaborative Law","year":2015,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Negotiation; Process (computing); Creativity; Legal profession; Legal research; Collaborative model; Legal education; Attendance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003630984,0.00009808895,0.0001777965,0.00005817393,0.0003869214,0.0001346024,0.0002968204,0.000124343,0.00006021747],"category_scores_gemma":[0.003725866,0.00008157364,0.00002249145,0.001899575,0.0009471645,0.000914406,0.00003602977,0.0002261388,0.00006133674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002606784,"about_ca_system_score_gemma":0.0007243414,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05265354,"about_ca_topic_score_gemma":0.1395089,"domain_scores_codex":[0.9979163,0.0005790289,0.0004919382,0.000183775,0.0005437649,0.0002851598],"domain_scores_gemma":[0.9977077,0.0002614101,0.0002621659,0.0001662749,0.001518834,0.00008357548],"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":[0.00008022672,0.00004553635,0.005690148,0.000002645167,0.000005825048,0.000002000629,0.006346924,0.0001438031,0.000508577,0.9867972,0.0001635131,0.0002136522],"study_design_scores_gemma":[0.0008758075,0.0002652173,0.001232311,0.0002611486,0.00003406206,0.000004099772,0.09571132,0.0004044465,0.06507584,0.4033029,0.4322459,0.000586902],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8929791,0.0001419763,0.0002311385,0.002473305,0.0003287266,0.00056785,0.000009081614,0.00005297478,0.1032159],"genre_scores_gemma":[0.9988347,0.00000601394,0.0001772535,0.000570956,0.0002447063,0.00003625423,0.000009464424,0.000008116457,0.0001125115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5834942,"threshold_uncertainty_score":0.9536549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03676786408899329,"score_gpt":0.3452354200430811,"score_spread":0.3084675559540878,"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."}}