{"id":"W6989137388","doi":"","title":"Alberta's carbon levy drives renewable fuel innovation to diversify economy, create jobs and reduce emissions","year":2016,"lang":"en","type":"other","venue":"","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Renewable energy; Greenhouse gas; Carbon fibers; Production (economics); Low-carbon economy; Carbon tax","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":[0.001178212,0.0004940983,0.0002810784,0.001717136,0.00930097,0.007542178,0.001353603,0.004641903,0.03634034],"category_scores_gemma":[0.002776467,0.0003259202,0.0005956346,0.001883983,0.002226673,0.000896639,0.002057591,0.00269311,0.00236316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07238416,"about_ca_system_score_gemma":0.1938717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9871042,"about_ca_topic_score_gemma":0.9956476,"domain_scores_codex":[0.998061,0.00008091459,0.00001909827,0.00008697565,0.001148263,0.0006036765],"domain_scores_gemma":[0.9980633,0.0001484931,0.00003816235,0.00005947794,0.001140508,0.0005500898],"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":[0.00009972152,0.0001109538,0.007083501,0.0001377293,0.00003024567,0.0003280681,0.0007553379,0.001902932,0.0008720943,0.2063948,0.7164633,0.06582128],"study_design_scores_gemma":[0.00005855433,0.00002340676,0.01756245,0.0001303325,0.0000311055,0.00006773965,0.001722427,0.001679281,0.0008871157,0.01409154,0.9636943,0.00005182533],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02027368,0.001630446,0.0008179357,0.04529695,0.0008194676,0.0001000862,0.002425258,0.0002926076,0.9283435],"genre_scores_gemma":[0.1178305,0.001493169,0.001523635,0.009441118,0.0001537726,0.00004461121,0.0009607516,0.00008930588,0.8684632],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07238416,"threshold_uncertainty_score":0.5251863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01766217784912057,"score_gpt":0.2866855526034077,"score_spread":0.2690233747542871,"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."}}