{"id":"W6927021107","doi":"10.3389/fpubh.2024.1248905.s001","title":"Data_Sheet_1_Cohort profile: the British Columbia COVID-19 Cohort (BCC19C)—a dynamic, linked population-based cohort.docx","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Mycobacterium research and diagnosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cohort; Cohort study; Selection (genetic algorithm); Work (physics); Cohort effect; MEDLINE","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003037311,0.001044137,0.001231048,0.004174264,0.001679173,0.002037153,0.001577515,0.001414252,0.4642268],"category_scores_gemma":[0.02597068,0.001184656,0.0006977737,0.005763213,0.0004704992,0.001707361,0.001475023,0.001503705,0.09824776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003396511,"about_ca_system_score_gemma":0.008819746,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1710014,"about_ca_topic_score_gemma":0.2101554,"domain_scores_codex":[0.998415,0.0002699154,0.0003376911,0.0002955259,0.0004564287,0.0002254692],"domain_scores_gemma":[0.9886537,0.003331773,0.001274538,0.001116576,0.004644614,0.0009788263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001236318,0.00001630344,0.002097714,0.0004660021,0.00001197689,0.00001976216,0.00003124192,0.00007738012,0.00004903938,0.0003303062,0.9923212,0.004455452],"study_design_scores_gemma":[0.002038681,0.0001100093,0.05667348,0.002834842,0.00006063544,0.000294559,0.0003581935,0.0005608234,0.0004457331,0.003012895,0.9334952,0.0001150106],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002835545,0.00003258503,0.0002341571,0.0002904851,0.00008165504,0.0007132343,0.9947949,0.0001858472,0.003383493],"genre_scores_gemma":[0.00440623,0.0002829684,0.003122069,0.001869063,0.0002345047,0.01146677,0.958137,0.0005213862,0.01996003],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8289986,"threshold_uncertainty_score":0.7642154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02770385591728135,"score_gpt":0.3229617938600324,"score_spread":0.2952579379427511,"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."}}