{"id":"W7036500192","doi":"","title":"Canada Invests in Greener, More Affordable Electricity Distribution for Ontario - Commodities (COMMODIT) News","year":2019,"lang":"en","type":"other","venue":"","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Distribution (mathematics); Electricity; Mains electricity; Government (linguistics); Work (physics)","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":[0.001873634,0.0006505639,0.0005950612,0.002729835,0.003403824,0.007007321,0.001111832,0.001535153,0.222299],"category_scores_gemma":[0.01469803,0.0005794505,0.001060794,0.005449724,0.001038184,0.001219278,0.001109772,0.002051507,0.03849188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03258841,"about_ca_system_score_gemma":0.08311217,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9771814,"about_ca_topic_score_gemma":0.9906031,"domain_scores_codex":[0.996765,0.00009183555,0.00007225834,0.0001885729,0.002337013,0.0005452856],"domain_scores_gemma":[0.9841113,0.00130961,0.0006309471,0.0006455826,0.01100104,0.00230157],"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":[0.00004688143,0.000008401826,0.001779984,0.00007569769,0.000009855215,0.00002605627,0.00003644318,0.00007347368,0.00005953638,0.001359395,0.9870064,0.009517903],"study_design_scores_gemma":[0.00002960663,0.00001044186,0.01543372,0.0001028479,0.00001823071,0.00002093578,0.0002460756,0.0003708093,0.0002553207,0.0006833439,0.9828004,0.00002826483],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.005581238,0.001443377,0.001920245,0.03485531,0.003685046,0.0002960945,0.5702313,0.003423065,0.3785643],"genre_scores_gemma":[0.03395928,0.002194682,0.005390468,0.009377065,0.0007111693,0.0002098674,0.1491863,0.002369285,0.7966019],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.222299,"threshold_uncertainty_score":0.7436641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01427356098452699,"score_gpt":0.2194111768474237,"score_spread":0.2051376158628967,"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."}}