{"id":"W4205999150","doi":"10.1163/9789004322714_cclc_2018-0194-005","title":"Carbon and Greenhouse Gas Legislation in Manitoba","year":2019,"lang":"en","type":"dataset","venue":"Climate Change and Law Collection","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Legislation; Greenhouse gas; Carbon fibers; Environmental science; Political science; Law; Computer science; Geology; Oceanography","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":[0.0001029331,0.0002112041,0.0002080692,0.00001822175,0.0001394736,0.00003553643,0.00006176237,0.000240776,0.0001257338],"category_scores_gemma":[0.000002318358,0.0002132649,0.00002101427,0.0001510394,0.0001421349,0.0001642167,0.0002078171,0.0001869792,0.00003863264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002913775,"about_ca_system_score_gemma":0.000001788219,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0227272,"about_ca_topic_score_gemma":0.0465097,"domain_scores_codex":[0.9990205,0.00003791281,0.0001651106,0.0003841289,0.0001470741,0.0002453318],"domain_scores_gemma":[0.999651,0.00001662576,0.00009911034,0.0001762217,0.000001322705,0.00005577329],"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":[0.0004497134,0.0008370618,0.1667622,0.0009585533,0.00006942117,0.000162354,0.002263719,0.001595323,0.0002433766,0.00008166603,0.8026491,0.02392757],"study_design_scores_gemma":[0.0009472036,0.0004499709,0.04384562,0.000125892,0.00009169558,0.00005354838,0.0003370884,0.01018531,0.000004260631,0.0001471942,0.9431481,0.0006641034],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.7605792,0.0009164241,0.00001015264,0.0002205755,0.00111937,0.002306292,0.2291786,0.00006903032,0.005600379],"genre_scores_gemma":[0.05989432,0.0910403,0.000430662,0.001581761,0.0007206102,0.000525377,0.8443397,0.0001563519,0.00131093],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.7006849,"threshold_uncertainty_score":0.9837806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02559077969564582,"score_gpt":0.2194057377863366,"score_spread":0.1938149580906908,"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."}}