{"id":"W2249063344","doi":"10.1177/0020731415621458","title":"Public Health Adaptation to Climate Change in Large Cities","year":2015,"lang":"en","type":"article","venue":"International Journal of Health Services","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Greater London Authority; University of Guelph; McGill University","keywords":"Urbanization; Public health; Climate change; Environmental planning; Urban climate; Adaptation (eye); Environmental resource management; Climate change adaptation; Business; Baseline (sea); Geography; Environmental health; Economic growth; Political science; Medicine; Economics; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003118214,0.0001045898,0.0002483025,0.0002866087,0.00007349146,0.00006713504,0.0003965786,0.00003533031,0.0002586688],"category_scores_gemma":[0.00003252709,0.00009352775,0.00003424279,0.0002347364,0.00001354716,0.0008671608,0.000159275,0.0001417178,0.0001638662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001075748,"about_ca_system_score_gemma":0.0001583107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0054025,"about_ca_topic_score_gemma":0.01651641,"domain_scores_codex":[0.9975837,0.0001553,0.0007855577,0.0001327675,0.0008019961,0.0005406986],"domain_scores_gemma":[0.9984275,0.00003645644,0.0006926155,0.00008502424,0.0001206984,0.000637729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002725541,0.0005669302,0.5525516,0.0002976981,0.00001800282,0.00006122226,0.2310805,0.0006195774,0.0000109519,0.0006818558,0.004004932,0.2098342],"study_design_scores_gemma":[0.002413379,0.00123537,0.8837407,0.001102009,0.000002208789,0.0001287606,0.02672189,0.003120675,0.000005122421,0.001359266,0.07994438,0.0002262874],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8030858,0.001403409,0.0002072156,0.1925111,0.001630631,0.0003548474,0.00006883467,0.00001897709,0.0007191853],"genre_scores_gemma":[0.9484996,0.001238899,0.0008747716,0.04897436,0.0003636817,0.00000985647,0.00001947881,0.00001138442,0.000007973274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.331189,"threshold_uncertainty_score":0.9216543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2290431411771258,"score_gpt":0.4026688661567289,"score_spread":0.1736257249796031,"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."}}