{"id":"W2947760904","doi":"10.5210/ojphi.v11i1.9676","title":"Lessons Learned from an Extreme Heat Event using ACES for Situational Awareness, Ontario, Canada","year":2019,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Health and Long-Term Care; Government of Ontario","keywords":"Medicine; Public health; Public health surveillance; Emergency department; Health care; Environmental health; Acute care; Medical emergency; Nursing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001715223,0.0001510175,0.0003749705,0.00008232774,0.0002424803,0.00007321199,0.0002950488,0.00007173567,0.001723573],"category_scores_gemma":[0.0001518608,0.000127546,0.00005874144,0.0001492351,0.00002687042,0.001274255,0.00007537029,0.0002802703,0.000009451413],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003022026,"about_ca_system_score_gemma":0.006453519,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6973331,"about_ca_topic_score_gemma":0.9503779,"domain_scores_codex":[0.9972006,0.00006789448,0.001332035,0.00009012627,0.0007310768,0.000578256],"domain_scores_gemma":[0.9978015,0.0001397137,0.0009421402,0.0002022424,0.0001125485,0.0008018646],"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":[0.0002122864,0.001453607,0.5967076,0.0008871607,0.0001298847,0.000009770107,0.04612258,0.07529603,0.0003995794,0.0001920424,0.06536389,0.2132255],"study_design_scores_gemma":[0.003128601,0.00113472,0.2532048,0.0003796311,0.00003186161,0.00009083,0.01158416,0.2215626,0.00002157188,0.0009896372,0.5073752,0.0004963765],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9612714,0.00006231335,0.004161366,0.03326426,0.0005524919,0.0002867286,0.0003254396,0.000006387363,0.00006959919],"genre_scores_gemma":[0.9060997,0.0005189385,0.06602956,0.02518513,0.000786762,0.000005943624,0.001044082,0.00004677469,0.0002831239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4420114,"threshold_uncertainty_score":0.999189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3482658844136833,"score_gpt":0.4128898646128001,"score_spread":0.0646239801991168,"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."}}