{"id":"W7011263155","doi":"","title":"Legal Information in Digital Form : The Challenge of Accessing Computerized Court Records.","year":2019,"lang":"en","type":"other","venue":"Archipelago (University of Quebec in Montreal)","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public access; Economic Justice; Task (project management); Reflection (computer programming); Information access; Face (sociological concept); Access to information; Legal research","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000410012,0.0001388513,0.0003740401,0.0003909729,0.0001038124,0.00005300328,0.0007837134,0.0002237428,0.0001931285],"category_scores_gemma":[0.00006299562,0.0001418332,0.0001059653,0.000286569,0.0006708142,0.001140888,0.0001780341,0.0002640348,0.00005147727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001334931,"about_ca_system_score_gemma":0.0002692034,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8617073,"about_ca_topic_score_gemma":0.9870241,"domain_scores_codex":[0.9988293,0.0001075056,0.0002789075,0.0001614795,0.000364118,0.0002586936],"domain_scores_gemma":[0.9989017,0.0002312049,0.0004971601,0.0002714123,0.0000559455,0.00004256225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001417692,0.0001228612,0.0009253291,0.0001125318,0.00003816641,0.00001389524,0.1930466,0.00009539641,0.000001117639,0.04621016,0.00684111,0.752451],"study_design_scores_gemma":[0.001655545,0.0002059968,0.01284005,0.002205252,0.00006506069,0.000001287935,0.3705479,0.00590177,0.000006310962,0.06656583,0.5389789,0.001026135],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04594455,0.00006352516,0.001329903,0.001249804,0.0003126517,0.0007145608,0.0000650026,0.00004253851,0.9502774],"genre_scores_gemma":[0.9403706,0.0004052148,0.0004033895,0.00002708314,0.00007902395,6.922992e-7,0.00003799752,0.00003528103,0.05864068],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8944261,"threshold_uncertainty_score":0.5783789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02022612662178799,"score_gpt":0.2542313723580985,"score_spread":0.2340052457363105,"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."}}