{"id":"W7093686818","doi":"","title":"Canadian Energy Transformation: Unexpected Winners Emerge. What You Need To Know","year":2025,"lang":"en","type":"other","venue":"","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Need to know; Energy (signal processing); Energy policy; Government (linguistics); Term (time)","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":[0.004452949,0.00141676,0.0008373672,0.002006502,0.01250933,0.01221806,0.003174769,0.008817228,0.1629736],"category_scores_gemma":[0.009625194,0.000450096,0.001113357,0.004023481,0.004065978,0.007438776,0.004713201,0.007574459,0.04068496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04501737,"about_ca_system_score_gemma":0.2111719,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9370803,"about_ca_topic_score_gemma":0.9782398,"domain_scores_codex":[0.9935942,0.0003177846,0.0001169301,0.0002098892,0.003484575,0.002276637],"domain_scores_gemma":[0.984897,0.0006189577,0.0001790896,0.0003106313,0.008471679,0.00552268],"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":[0.00001047977,0.000007863703,0.0001280185,0.00008398763,0.000002804542,0.00002853858,0.0000579642,0.00002784608,0.0000403624,0.005355144,0.9776785,0.0165786],"study_design_scores_gemma":[0.000004289835,0.00000374516,0.000577245,0.0001702177,0.000003703653,0.00001473507,0.0007433522,0.00003726233,0.00005095013,0.001836309,0.9965426,0.00001559067],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.001347672,0.03015316,0.000725244,0.629136,0.03396041,0.00008905153,0.007784229,0.0009393764,0.2958648],"genre_scores_gemma":[0.03025359,0.05268567,0.003401932,0.1568893,0.004440353,0.0001391791,0.009330477,0.0009742135,0.7418852],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1629736,"threshold_uncertainty_score":0.5452011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005795198244229357,"score_gpt":0.2452469640541163,"score_spread":0.2394517658098869,"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."}}