{"id":"W6980817275","doi":"","title":"CROSS-COMPARING OECD COUNTRIES ON CARBON EMISSION POLICY IMPLEMENTATION GAP","year":2024,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Policy Transfer and Learning","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Greenhouse gas; Climate policy; Carbon fibers; Politics; Global warming; Climate change mitigation; Public policy","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":[0.004200289,0.0002587933,0.0003789726,0.002292657,0.00083934,0.001674736,0.0003530057,0.0003947669,0.002663276],"category_scores_gemma":[0.01183788,0.00009838551,0.0004176614,0.004736441,0.000866073,0.001373201,0.003143936,0.0004645129,0.0002745292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001859068,"about_ca_system_score_gemma":0.001721666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02620183,"about_ca_topic_score_gemma":0.02085405,"domain_scores_codex":[0.9959651,0.001817785,0.0002943549,0.0002261174,0.0007913616,0.00090536],"domain_scores_gemma":[0.9944515,0.002173056,0.001043321,0.00055654,0.001566046,0.0002095115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00103373,0.00048039,0.8147832,0.0005269846,0.0007048586,0.001147853,0.01219759,0.01180049,0.001175411,0.04302498,0.008822693,0.1043019],"study_design_scores_gemma":[0.00005365765,0.0002113927,0.9465023,0.0002293351,0.0001263458,0.0001624181,0.02242911,0.001169056,0.001786811,0.002791042,0.02449727,0.00004140984],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9532498,0.0009691558,0.0007362044,0.0006494503,0.00003431911,0.00005671431,0.001253819,0.00002306642,0.04302747],"genre_scores_gemma":[0.9961147,0.0005499423,0.0003637322,0.0002206618,0.000008489272,0.0001017326,0.001621055,0.0000104587,0.001009255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02620183,"threshold_uncertainty_score":0.05209863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0313625526651229,"score_gpt":0.3453966873661649,"score_spread":0.314034134701042,"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."}}