{"id":"W4240817101","doi":"10.1163/9789004322714_cclc_2017-0028-008","title":"Ontario’s major parties show that carbon pricing is a nonpartisan issue But the right path forward must consider the big picture","year":2018,"lang":"en","type":"dataset","venue":"Climate Change and Law Collection","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Path (computing); Computer science; Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00166164,0.001627361,0.001064513,0.003848963,0.001711957,0.0033125,0.00295909,0.002638116,0.03710208],"category_scores_gemma":[0.01264133,0.0007754294,0.001492042,0.008078879,0.0008893527,0.001248993,0.001919626,0.002267865,0.03169787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009890304,"about_ca_system_score_gemma":0.0154827,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7634765,"about_ca_topic_score_gemma":0.8893802,"domain_scores_codex":[0.9981824,0.0001917456,0.0001193283,0.0002621891,0.0007521139,0.0004922301],"domain_scores_gemma":[0.9935923,0.001095574,0.0006852955,0.001223937,0.002751677,0.0006510419],"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":[0.00003511593,0.00001120194,0.00208116,0.0001360406,0.00002015387,0.0000145586,0.00002205613,0.000166648,0.00001967679,0.0005480087,0.9960979,0.0008474545],"study_design_scores_gemma":[0.0001993148,0.000008050264,0.01987304,0.0003203885,0.00004142939,0.00004225106,0.0001684464,0.0007149733,0.0002051797,0.001179719,0.9772165,0.00003069118],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003397033,0.00005987295,0.00004282858,0.0003780608,0.00003674761,0.000008502633,0.9976072,0.0001199983,0.001407065],"genre_scores_gemma":[0.001663233,0.00009313331,0.0002138199,0.0001560386,0.00001567329,0.00005167061,0.9948561,0.00006107628,0.002889209],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2365235,"threshold_uncertainty_score":0.4758329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1329639330284514,"score_gpt":0.3210753895513692,"score_spread":0.1881114565229177,"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."}}