{"id":"W2625967724","doi":"10.25071/2564-4033.40177","title":"Health Equity, Population Health, and Climate Change Adaptation in Ontario, Canada","year":2015,"lang":"en","type":"article","venue":"Health Tomorrow Interdisciplinarity and Internationality","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"National Institute on Minority Health and Health Disparities","keywords":"Health equity; Climate change; Equity (law); Public health; Population health; Political science; Public economics; Work (physics); Public relations; Environmental resource management; Economic growth; Medicine; Economics; Nursing; Ecology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001671653,0.0001688634,0.0002796644,0.001047464,0.01329281,0.002749175,0.0009648936,0.0005140699,0.002810674],"category_scores_gemma":[0.003397471,0.0002080009,0.0002336497,0.003815127,0.004127924,0.0008079123,0.001954697,0.0008654728,0.00007036134],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1703398,"about_ca_system_score_gemma":0.2570065,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9992161,"about_ca_topic_score_gemma":0.9997742,"domain_scores_codex":[0.9984007,0.0002734622,0.00005351713,0.00009592994,0.0004838736,0.0006923525],"domain_scores_gemma":[0.99689,0.0005286956,0.0003545432,0.0000606176,0.001118619,0.001047525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001702826,0.0001902653,0.4603821,0.0008945751,0.0001014354,0.001291658,0.3434175,0.0023536,0.001299128,0.05017719,0.03566639,0.1040559],"study_design_scores_gemma":[0.00002179458,0.0000452153,0.6942559,0.0005242469,0.00004239762,0.0001026409,0.2113852,0.0008666201,0.000230276,0.00308931,0.089377,0.00005940108],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8659474,0.009085874,0.0006631936,0.03633653,0.0001160427,0.0001729774,0.001198106,0.00002824856,0.08645169],"genre_scores_gemma":[0.9925136,0.002495687,0.0003381484,0.0005954709,0.000009730291,0.00002735588,0.000114196,0.000005122054,0.003900714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1703398,"threshold_uncertainty_score":0.9622883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1794440360077973,"score_gpt":0.3923548635384981,"score_spread":0.2129108275307009,"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."}}