{"id":"W4394334888","doi":"10.6084/m9.figshare.19367255","title":"Additional file 5 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); Healthcare system; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Psychological resilience; 2019-20 coronavirus outbreak; Health care; Geography; Virology; Economic growth; Medicine; Psychology; Economics; Social psychology; Alternative 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":[0.002096933,0.0009194463,0.0009511458,0.002642883,0.0008912248,0.001632613,0.0019103,0.001501184,0.4931706],"category_scores_gemma":[0.01928467,0.000733691,0.001039406,0.005674114,0.0003511062,0.001541936,0.001505349,0.001447964,0.06753358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002255327,"about_ca_system_score_gemma":0.0041197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04871662,"about_ca_topic_score_gemma":0.08004995,"domain_scores_codex":[0.9988598,0.0002678022,0.0002706604,0.0002166909,0.0001919077,0.0001931559],"domain_scores_gemma":[0.989621,0.005114816,0.001146607,0.0008277898,0.002816812,0.0004729058],"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":[0.00008146574,0.00003885507,0.002122753,0.001211006,0.00003291212,0.00001761585,0.00005667857,0.0002814292,0.00001705562,0.0007117637,0.9934452,0.00198335],"study_design_scores_gemma":[0.002646744,0.0001267253,0.04271137,0.003684461,0.0001876147,0.0001136729,0.001096361,0.0009357752,0.0002804064,0.00514617,0.9429587,0.0001120718],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008586248,0.000009744662,0.00003549084,0.00005061222,0.000006095304,0.00006225409,0.9993926,0.0000199667,0.0003372996],"genre_scores_gemma":[0.003081049,0.00007365931,0.0008865334,0.0002238173,0.00001870807,0.003426451,0.9882761,0.0000733366,0.003940325],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4931706,"threshold_uncertainty_score":0.7229307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0981754017018771,"score_gpt":0.4020437749007034,"score_spread":0.3038683731988263,"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."}}