{"id":"W2158926612","doi":"10.1186/1476-072x-10-7","title":"Modelling the variation of land surface temperature as determinant of risk of heat-related health events","year":2011,"lang":"en","type":"article","venue":"International Journal of Health Geographics","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sante Montreal; Université de Montréal; Natural Resources Canada; BC Centre for Disease Control; Institut National de Santé Publique du Québec; Montreal Police Service","funders":"Health Canada","keywords":"Variation (astronomy); Health geography; Public health; Health informatics; Human geography; Econometrics; Physical geography; Environmental science; Statistics; Geography; Mathematics; Medicine; Health policy; Economic geography; International health","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":[],"consensus_categories":[],"category_scores_codex":[0.002605256,0.0001058167,0.0003396857,0.0001436957,0.00009639622,0.000004661785,0.0003677177,0.00008006404,0.0001415231],"category_scores_gemma":[0.00008517455,0.00007297102,0.0001337044,0.0002650534,0.0001010112,0.000160935,0.00006144101,0.0003240306,0.000002293557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009841012,"about_ca_system_score_gemma":0.0001692635,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01623006,"about_ca_topic_score_gemma":0.000313442,"domain_scores_codex":[0.9973719,0.0002654727,0.001278475,0.000105939,0.0007580623,0.0002201859],"domain_scores_gemma":[0.997232,0.0001670861,0.002105694,0.0001468716,0.0002092634,0.0001391358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005620704,0.0007608834,0.8509446,0.0002067056,0.0002023214,0.000007493838,0.0279667,0.1137675,0.000395288,0.0003177804,0.000228769,0.004639838],"study_design_scores_gemma":[0.001624799,0.001494601,0.9695405,0.001075775,0.00005079954,0.0001377926,0.0008385293,0.01627313,0.0004544935,0.00819481,0.0001656714,0.0001491497],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958369,0.001112597,0.0005269698,0.001723126,0.000479054,0.0001753725,0.00008065302,0.000002911936,0.00006247783],"genre_scores_gemma":[0.9889982,0.009618741,0.001091901,0.0002400713,0.00003038521,5.623103e-7,0.000006604715,0.000009353603,0.000004196445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1185958,"threshold_uncertainty_score":0.9903209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04462598320827266,"score_gpt":0.3143584138599452,"score_spread":0.2697324306516726,"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."}}