{"id":"W3201949809","doi":"10.1016/j.erss.2021.102237","title":"Energy poverty in Canada: Prevalence, social and spatial distribution, and implications for research and policy","year":2021,"lang":"en","type":"article","venue":"Energy Research & Social Science","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research","keywords":"Poverty; Distribution (mathematics); Energy poverty; Geography; Regional science; Socioeconomics; Political science; Economic growth; Sociology; Economics; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.001792013,0.0001124992,0.0001394746,0.00009495401,0.002365947,0.0001443714,0.000299375,0.00008406498,0.00006586828],"category_scores_gemma":[0.0006018803,0.0001109972,0.00001517254,0.001571849,0.002844791,0.0003321958,0.0009178474,0.0002271197,7.305259e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001597738,"about_ca_system_score_gemma":0.001310703,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7813634,"about_ca_topic_score_gemma":0.8094528,"domain_scores_codex":[0.9969717,0.0002628019,0.0001742935,0.0006328469,0.0009363235,0.001022029],"domain_scores_gemma":[0.9990367,0.0003514551,0.00003196696,0.0001522927,0.00007988382,0.0003476761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001248286,0.0003062295,0.2247795,0.00005148748,0.00001744046,0.00002223371,0.001573099,0.000103292,0.032018,0.4094949,0.01803685,0.3134721],"study_design_scores_gemma":[0.0002901824,0.00006054486,0.9485971,0.000007027384,0.000001806023,0.000006522931,0.0002661408,0.0002184321,0.001285335,0.02334589,0.02578139,0.0001396773],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9674334,0.0003284816,0.0005328808,0.02099933,0.00005075787,0.0001778719,0.000186324,0.00001300582,0.01027795],"genre_scores_gemma":[0.9974204,0.0007621676,0.00004373968,0.0002452831,0.0001497448,0.00008199432,0.00001741957,0.000008647336,0.001270617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7238175,"threshold_uncertainty_score":0.9998689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05809625735834843,"score_gpt":0.3693707192140465,"score_spread":0.3112744618556981,"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."}}