{"id":"W4394405799","doi":"10.6084/m9.figshare.21825135","title":"Round 1 Delphi responses (de-identified) - COVID-19 vaccine consensus study (LMICs)","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre; University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Virology; Delphi method; Delphi; Medicine; Computer science; Infectious disease (medical specialty); Outbreak; Artificial intelligence; Disease","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":[],"consensus_categories":[],"category_scores_codex":[0.01850418,0.001014132,0.000779088,0.0026032,0.001358109,0.001463256,0.001759562,0.001200923,0.1116374],"category_scores_gemma":[0.06535441,0.0009049394,0.001099694,0.003343662,0.0004391747,0.001012893,0.002960017,0.002024204,0.02452249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003294083,"about_ca_system_score_gemma":0.009381664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02010582,"about_ca_topic_score_gemma":0.03363958,"domain_scores_codex":[0.9899513,0.005528009,0.001163984,0.00104153,0.001599182,0.0007159907],"domain_scores_gemma":[0.9733847,0.01314539,0.001590183,0.003250334,0.007953053,0.0006764103],"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":[0.0006365188,0.0001063109,0.003757559,0.003716691,0.0000798517,0.00006428655,0.001089615,0.000609253,0.0002815942,0.002787417,0.9637809,0.02309003],"study_design_scores_gemma":[0.001656752,0.0002094035,0.03067279,0.005061903,0.0001108787,0.00008915884,0.002888989,0.001043402,0.001003233,0.004407023,0.9527622,0.00009429758],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005367192,0.0001207442,0.003183325,0.0008619862,0.0001768355,0.01365444,0.9647232,0.0002316025,0.01168074],"genre_scores_gemma":[0.02756147,0.000256223,0.02921953,0.002301569,0.00007264387,0.3127588,0.6117363,0.0003089065,0.01578459],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1116374,"threshold_uncertainty_score":0.3734642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3867495433054716,"score_gpt":0.5382153007540272,"score_spread":0.1514657574485557,"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."}}