{"id":"W7045968595","doi":"","title":"Canada Invests in Clean Energy Research in Quebec - Commodities (COMMODIT) News","year":2019,"lang":"en","type":"other","venue":"","topic":"Global Energy Security and Policy","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Clean technology; Clean energy; Renewable energy; Government (linguistics); Energy (signal processing); Energy consumption","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":[0.001261763,0.0007064446,0.0004390916,0.001655814,0.004892834,0.007461064,0.001072133,0.004356097,0.1664324],"category_scores_gemma":[0.003483116,0.0004599324,0.0009180707,0.002173591,0.001218945,0.001324834,0.001400165,0.003646216,0.01964704],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05089303,"about_ca_system_score_gemma":0.1048248,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9791527,"about_ca_topic_score_gemma":0.9912997,"domain_scores_codex":[0.9978414,0.00007539617,0.00003194966,0.00009634713,0.00141462,0.0005402747],"domain_scores_gemma":[0.9960365,0.0002125868,0.00008531453,0.0001177221,0.002500192,0.001047592],"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":[0.00001840894,0.00001173299,0.0003342905,0.0000306831,0.000004020078,0.00003466382,0.00002084145,0.00005969299,0.00006923094,0.004838957,0.9865053,0.00807221],"study_design_scores_gemma":[0.000007523763,0.000003918595,0.001356195,0.00004476949,0.000003410507,0.0000105793,0.00007353952,0.00009676567,0.00009503543,0.0003195292,0.9979805,0.000008177247],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004782141,0.01100901,0.0006092789,0.1472211,0.01530075,0.0001597561,0.02223088,0.0008174743,0.7978697],"genre_scores_gemma":[0.0113427,0.002881996,0.0004354341,0.01039127,0.0005405444,0.00002024981,0.002245618,0.0001512735,0.971991],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.949107,"threshold_uncertainty_score":0.5567716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04469944527589535,"score_gpt":0.2932606663166763,"score_spread":0.2485612210407809,"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."}}