{"id":"W4394189473","doi":"10.6084/m9.figshare.19367243","title":"Additional file 1 of Healthcare system resilience in Bangladesh and Haiti in times of global changes (climate-related events, migration and Covid-19): an interdisciplinary mixed method research protocol","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Resilience (materials science); Coronavirus disease 2019 (COVID-19); Protocol (science); Pandemic; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Computer science; Geography; Biology; Virology; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001936331,0.0008576506,0.0007826743,0.002183025,0.0009207904,0.001327913,0.00160481,0.001301114,0.4962915],"category_scores_gemma":[0.01621487,0.0006604109,0.0008292011,0.004516683,0.0003234377,0.001444998,0.001292637,0.001233738,0.05510357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002168207,"about_ca_system_score_gemma":0.003976982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04239793,"about_ca_topic_score_gemma":0.07186229,"domain_scores_codex":[0.9991415,0.0001920877,0.000217072,0.0001716321,0.000133727,0.0001440635],"domain_scores_gemma":[0.9927902,0.003218186,0.000864442,0.0005684606,0.002212039,0.0003466169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009717279,0.00005131499,0.002855825,0.00141709,0.00002611746,0.00002263483,0.00009767487,0.0002545875,0.00002425868,0.0007265,0.9917048,0.002722065],"study_design_scores_gemma":[0.003333576,0.0002158489,0.07144903,0.005375119,0.0001990343,0.0001886439,0.001899146,0.00115106,0.0004068126,0.005615888,0.910023,0.0001429838],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000153271,0.00001043594,0.00005189077,0.00005871528,0.000006444612,0.0001542562,0.9991542,0.00001954868,0.0003911104],"genre_scores_gemma":[0.005001751,0.0001023015,0.001467671,0.0002982219,0.00002504327,0.009464652,0.9789738,0.00008111442,0.004585452],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4962915,"threshold_uncertainty_score":0.7184791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09964167960711222,"score_gpt":0.4024021678088172,"score_spread":0.3027604882017049,"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."}}