{"id":"W4210611871","doi":"10.2139/ssrn.3978047","title":"Leading Legal Disruption Editorial: A Vision for the Future of Artificial Intelligence","year":2021,"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":"Université du Québec; York University","funders":"","keywords":"Political science; Artificial intelligence; Computer science","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":[0.01476064,0.002746033,0.002689676,0.005549327,0.009112776,0.02583725,0.005008036,0.03088328,0.02334291],"category_scores_gemma":[0.06679305,0.0009346976,0.002554272,0.003867919,0.007557749,0.01001335,0.003751617,0.02453316,0.01133883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007522348,"about_ca_system_score_gemma":0.01408493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003870108,"about_ca_topic_score_gemma":0.009833857,"domain_scores_codex":[0.9853198,0.002976996,0.001578863,0.001742727,0.006883256,0.001498329],"domain_scores_gemma":[0.9163251,0.03591959,0.005579683,0.003065522,0.02749797,0.01161222],"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":[0.000009369758,0.000009486555,0.00002629579,0.0000728508,0.000005950484,0.00005793821,0.00003545839,0.00002552073,0.0000158821,0.001691116,0.9956111,0.002438977],"study_design_scores_gemma":[0.00003204748,0.0000204657,0.0001736757,0.0004196957,0.00003339059,0.00007941857,0.0003035834,0.0002369504,0.00008889845,0.007844849,0.9907386,0.00002833294],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00005856924,0.003936459,0.0001346713,0.1702768,0.8221654,0.00001111055,0.00004857557,0.00004958464,0.003318846],"genre_scores_gemma":[0.001967806,0.003083669,0.0002270322,0.05828018,0.923062,0.00001892526,0.00003096603,0.00005468074,0.01327469],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.03088328,"threshold_uncertainty_score":0.07808983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02462705828835988,"score_gpt":0.3669922899221706,"score_spread":0.3423652316338107,"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."}}