{"id":"W4414665079","doi":"10.1163/9789004322714_cclc_2022-0198-0716","title":"Canada Launches Greenhouse Gas Offset Credit System","year":2025,"lang":"en","type":"dataset","venue":"Climate Change and Law Collection","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Offset (computer science); Greenhouse; Carbon offset","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":[0.001336729,0.001873892,0.001436138,0.006439451,0.002006274,0.003609895,0.003038446,0.00208359,0.05263971],"category_scores_gemma":[0.008867582,0.00110593,0.001147552,0.01716622,0.0006338031,0.001354181,0.001509645,0.00240483,0.03216197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01829102,"about_ca_system_score_gemma":0.04386162,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9630297,"about_ca_topic_score_gemma":0.9727668,"domain_scores_codex":[0.9979916,0.0001225365,0.000124688,0.0002761999,0.0009769079,0.0005081692],"domain_scores_gemma":[0.9906927,0.0007304647,0.0006665759,0.0008020008,0.006144698,0.0009635768],"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":[0.00002609931,0.0000116651,0.001187866,0.00009058372,0.00001327566,0.000009094949,0.00001091633,0.0003177519,0.00001344344,0.0004457875,0.9967444,0.001129015],"study_design_scores_gemma":[0.0002231299,0.00001363316,0.02497664,0.0002377843,0.00003725845,0.00002572188,0.0001426471,0.00160605,0.000322515,0.00097183,0.9713859,0.00005683631],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.000182363,0.00003314367,0.00002266059,0.0001031794,0.00001171284,0.000007249242,0.9987193,0.00009050001,0.0008299547],"genre_scores_gemma":[0.001264201,0.00008743878,0.0001856808,0.00009224541,0.000008285216,0.00004340244,0.9950557,0.00005348198,0.003209593],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05263971,"threshold_uncertainty_score":0.1760974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07397755557796544,"score_gpt":0.2311394543114804,"score_spread":0.157161898733515,"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."}}