{"id":"W4243315014","doi":"10.4018/978-1-60566-060-8.ch164","title":"Free Access to Law and Open Source Software","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Duty; Legislation; Political science; Law; Public law; Work (physics); Public access; Legal research; Engineering; Public administration","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003744414,0.0003515553,0.0004954415,0.00004047464,0.0007806599,0.001658669,0.003103249,0.0005317995,0.0002716462],"category_scores_gemma":[0.0002042226,0.000375945,0.0001086388,0.00003463325,0.0006992316,0.0003184146,0.001655023,0.0002645114,0.0002930519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003200069,"about_ca_system_score_gemma":0.0003242876,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02442171,"about_ca_topic_score_gemma":0.1315119,"domain_scores_codex":[0.9977818,0.00005029093,0.0003737624,0.0006544971,0.0006179133,0.0005217541],"domain_scores_gemma":[0.9984089,0.0001019062,0.0001778169,0.0006554179,0.0001854644,0.0004705581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002280701,0.000005311909,0.00002116837,0.000004805624,0.0000197037,0.00002108917,0.0009012843,0.000003567415,4.839238e-7,0.9240484,0.008718015,0.06623334],"study_design_scores_gemma":[0.00002946056,0.00003756114,0.000005087424,0.00008842471,0.00002001512,0.000001252703,0.00009172251,2.821147e-7,0.00001546023,0.5154014,0.4840478,0.0002615145],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00005601797,0.0001178487,0.0004252088,0.0009708084,0.0003974886,0.001092059,0.0001542083,0.0002249006,0.9965615],"genre_scores_gemma":[0.1128599,0.00002649803,0.003526836,0.02809901,0.002286997,0.00006881551,0.000006486577,0.0001470407,0.8529784],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4753298,"threshold_uncertainty_score":0.9998692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07350246502985276,"score_gpt":0.3647598886459442,"score_spread":0.2912574236160915,"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."}}