{"id":"W4415578923","doi":"10.1093/eurpub/ckaf161.506","title":"From behavioural data to policy: How iCARE informed Canada’s pandemic preparedness response","year":2025,"lang":"en","type":"article","venue":"European Journal of Public Health","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centres Intégré Universitaires de Santé et de Services Sociaux; Université du Québec à Montréal","funders":"","keywords":"Context (archaeology); Pandemic; Agency (philosophy); Preparedness; Public health; Data collection; Resilience (materials science); Psychological resilience; Coronavirus disease 2019 (COVID-19)","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":[0.09489224,0.0013268,0.001144304,0.007527761,0.0143996,0.02232955,0.004667889,0.004783594,0.008134541],"category_scores_gemma":[0.1829568,0.001193819,0.001418791,0.007653059,0.0132758,0.006342259,0.01170068,0.01360904,0.0008724282],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.2902395,"about_ca_system_score_gemma":0.5581285,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9914852,"about_ca_topic_score_gemma":0.9931695,"domain_scores_codex":[0.9293761,0.04150303,0.002687239,0.00341589,0.01415524,0.00886252],"domain_scores_gemma":[0.8112609,0.07757711,0.003023481,0.009996199,0.08317344,0.01496887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003348763,0.0003130459,0.05149379,0.001704794,0.0004232224,0.001271672,0.0702742,0.02340973,0.00104471,0.2781813,0.3250394,0.2465093],"study_design_scores_gemma":[0.00008414088,0.0001255936,0.02636889,0.005833201,0.0002537551,0.00009154283,0.06297265,0.01556298,0.001761939,0.08254219,0.8037369,0.0006663329],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03141637,0.003782738,0.02100141,0.826166,0.002810505,0.001266155,0.006210108,0.0005813183,0.1067653],"genre_scores_gemma":[0.7632092,0.008616005,0.08940411,0.1065234,0.001192781,0.001220315,0.003716177,0.0005682769,0.02554979],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7097605,"threshold_uncertainty_score":0.8232216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.186094103043327,"score_gpt":0.4034289980609517,"score_spread":0.2173348950176247,"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."}}