{"id":"W4409583335","doi":"10.2139/ssrn.5204536","title":"Reducing CO2 emissions: Goodness of heart or insurance policy?&amp;nbsp;","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Goodness of fit; Actuarial science; Economics; Environmental science; Statistics; Mathematics","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":[0.006005998,0.0005817189,0.002094087,0.001238646,0.001043902,0.006088344,0.001025688,0.005754073,0.0185071],"category_scores_gemma":[0.03845341,0.0002191878,0.0006345868,0.001762232,0.003381621,0.005900753,0.001209379,0.00406008,0.001205368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002525457,"about_ca_system_score_gemma":0.002549489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02274171,"about_ca_topic_score_gemma":0.02038253,"domain_scores_codex":[0.9978896,0.0009601497,0.0001246664,0.000259823,0.0005349644,0.0002308418],"domain_scores_gemma":[0.9825684,0.01074168,0.002332282,0.0008035254,0.00216823,0.001385806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001512372,0.0003848344,0.02949991,0.0009729799,0.001396526,0.0002108181,0.000281527,0.0115263,0.0008690028,0.4362216,0.3010452,0.2160789],"study_design_scores_gemma":[0.0002266454,0.0001740798,0.0226026,0.0006774792,0.0005366654,0.0001162184,0.001553964,0.01915711,0.001511182,0.8809752,0.07235239,0.0001163066],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06159892,0.02689978,0.008144225,0.7723222,0.00953498,0.00004108791,0.001540516,0.000237325,0.119681],"genre_scores_gemma":[0.9249346,0.01260218,0.003635859,0.03682625,0.007987498,0.00002966537,0.0002689097,0.0002685207,0.01344649],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02274171,"threshold_uncertainty_score":0.06191242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08956874762883693,"score_gpt":0.3158911540409421,"score_spread":0.2263224064121052,"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."}}