{"id":"W4394300201","doi":"10.6084/m9.figshare.21206605","title":"Additional file 1 of Public health genomics capacity assessment: readiness for large-scale pathogen genomic surveillance in Canada’s public health laboratories","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Zoonotic diseases and public health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Public Health Agency of Canada","funders":"","keywords":"Public health; Genomics; Scale (ratio); Public health surveillance; Environmental health; Data science; Business; Biology; Genome; Computer science; Medicine; Genetics; Geography; Gene","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00202262,0.001223364,0.001272981,0.004167813,0.002008045,0.002986427,0.002840666,0.001439384,0.4250669],"category_scores_gemma":[0.022186,0.0007312117,0.001370223,0.01037355,0.0006107949,0.001369075,0.001803451,0.001618421,0.04962082],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01094134,"about_ca_system_score_gemma":0.02077868,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7363089,"about_ca_topic_score_gemma":0.8174178,"domain_scores_codex":[0.998667,0.0001783511,0.0001759085,0.0002997608,0.0003552476,0.000323736],"domain_scores_gemma":[0.9806157,0.008912633,0.001063771,0.001161933,0.00714653,0.001099506],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00005923516,0.00001676136,0.002435172,0.0009407906,0.00002987335,0.00001473482,0.00004485903,0.000252007,0.00001457343,0.0003928466,0.9942613,0.001537898],"study_design_scores_gemma":[0.00157878,0.00004114956,0.04806736,0.003425595,0.0001680891,0.0001005656,0.0007929773,0.001166228,0.0002973672,0.002466693,0.9417792,0.0001160859],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003883338,0.000008111664,0.00001283086,0.00002759845,0.000003564739,0.00001040008,0.9996792,0.00001837912,0.0002011124],"genre_scores_gemma":[0.001705445,0.00006446037,0.0004530994,0.0001123618,0.00001069415,0.0003253686,0.9954311,0.00006590021,0.001831689],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9979774,"threshold_uncertainty_score":0.8200724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0681389240874697,"score_gpt":0.3000548267701934,"score_spread":0.2319159026827237,"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."}}