{"id":"W4387935660","doi":"10.51189/coninters2023/24330","title":"COMERCIO DE CRÉDITO DE CARBONO: ANÁLISE DE ISENÇÃO TRIBUTÁRIA COMO INCENTIVO DO DESENVOLVIMENTO SUSTENTÁVEL","year":2023,"lang":"pt","type":"article","venue":"","topic":"Urban Arborization and Environmental Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Compute Canada","funders":"","keywords":"Political science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000943751,0.0005929973,0.0005110551,0.000143772,0.0007619826,0.0002139784,0.0006754964,0.0002942066,0.009749638],"category_scores_gemma":[0.0000951441,0.0006065447,0.0002558787,0.001104882,0.0006511716,0.0003303743,0.001231787,0.0003830334,0.005718471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003678703,"about_ca_system_score_gemma":0.00008145696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002591311,"about_ca_topic_score_gemma":0.0008380412,"domain_scores_codex":[0.9955139,0.0003395263,0.000613109,0.0008649616,0.0007832002,0.001885375],"domain_scores_gemma":[0.998243,0.0001571951,0.0001837461,0.0005893799,0.00001242234,0.0008141969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008509263,0.0005880354,0.8011132,0.00006115877,0.0001702566,0.0001452863,0.004918573,0.002560894,0.01661764,0.0002823479,0.1716485,0.001808952],"study_design_scores_gemma":[0.002525855,0.0002314987,0.8957794,0.00009929787,0.0002389227,0.00002390662,0.01317003,0.02998095,0.006143648,0.0005465027,0.05002993,0.001230069],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9594288,0.001092743,0.002826849,0.004213266,0.00112778,0.001107969,0.000247941,0.0005233646,0.02943121],"genre_scores_gemma":[0.9525683,0.002388698,0.0004424614,0.001250942,0.0001933705,0.00008342075,0.00007340238,0.00008784739,0.04291159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1216186,"threshold_uncertainty_score":0.9996386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01899827742971485,"score_gpt":0.2501002611140072,"score_spread":0.2311019836842923,"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."}}