{"id":"W7106509758","doi":"10.20944/preprints202511.1753.v1","title":"Carbon Price Certainty and Green Innovation: Evidence from Canada’s Federal Backstop Policy","year":2025,"lang":"","type":"preprint","venue":"Preprints.org","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Certainty; Core (optical fiber); Carbon price; Legislature; Emission intensity; Greenhouse gas; Carbon fibers; Emissions trading","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":[0.004038402,0.0003230202,0.000596491,0.001389901,0.002823944,0.003613928,0.0016109,0.001441156,0.003331219],"category_scores_gemma":[0.01886543,0.0002594181,0.0007904246,0.003476788,0.003153374,0.0008840056,0.001566667,0.002169307,0.0002621083],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04737509,"about_ca_system_score_gemma":0.07612359,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9937673,"about_ca_topic_score_gemma":0.9939163,"domain_scores_codex":[0.9940996,0.0006230869,0.0001816329,0.0005497123,0.002707573,0.001838304],"domain_scores_gemma":[0.9656323,0.01264232,0.007697062,0.00159715,0.008863874,0.003567266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001939899,0.0006906328,0.9038646,0.0004533113,0.0007328494,0.0005139626,0.003191116,0.009746647,0.00110652,0.0148323,0.01660681,0.04632134],"study_design_scores_gemma":[0.0001416369,0.0002378277,0.97284,0.0001162864,0.0003294801,0.00002927403,0.00351362,0.003269703,0.0008671,0.00128418,0.0172928,0.00007814438],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.942013,0.003687897,0.0005779963,0.008347244,0.00006831917,0.0001250726,0.005422334,0.00005739756,0.03970068],"genre_scores_gemma":[0.9937343,0.0009461839,0.0001335013,0.0006939364,0.00002233294,0.00001366051,0.001108369,0.000006327456,0.0033414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9526249,"threshold_uncertainty_score":0.3437319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.108641504682695,"score_gpt":0.3596812342820089,"score_spread":0.2510397295993139,"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."}}