{"id":"W6960734898","doi":"10.1371/journal.pone.0150176.t002","title":"Number of total and linked records and unique individuals in various data sources constituting the BC-HTC, Canada.","year":2016,"lang":"en","type":"dataset","venue":"Figshare","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Record linkage; Data source; Identification (biology); Data collection; Data set","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":[],"consensus_categories":[],"category_scores_codex":[0.00100509,0.001472204,0.00172317,0.005867112,0.001998627,0.002829677,0.003409223,0.0009867164,0.04461198],"category_scores_gemma":[0.009616407,0.0008475335,0.000943903,0.01840834,0.0007129653,0.0008889469,0.001626679,0.002048571,0.0273818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01366135,"about_ca_system_score_gemma":0.04145617,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.926657,"about_ca_topic_score_gemma":0.9591849,"domain_scores_codex":[0.9985855,0.00008383612,0.0001324365,0.0003611445,0.000567303,0.0002697137],"domain_scores_gemma":[0.9923286,0.0009087548,0.0005386613,0.0008558432,0.004470278,0.000897884],"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":[0.0000453404,0.000007149407,0.002006873,0.0004193287,0.00004668152,0.00001395971,0.00003357541,0.0002200918,0.00005641213,0.0005474531,0.9943826,0.002220519],"study_design_scores_gemma":[0.0001811797,0.000005206338,0.02010418,0.0005682204,0.00007539706,0.00003810617,0.0001594275,0.000352794,0.000318578,0.0007811164,0.9773702,0.00004565106],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007660905,0.00003702699,0.00002299618,0.00002290252,0.000007044231,0.000004923893,0.9992982,0.00005340314,0.0004768262],"genre_scores_gemma":[0.0006844064,0.00009169984,0.0002672882,0.00003065716,0.000003759948,0.00003042131,0.9976915,0.0000465337,0.001153763],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07334298,"threshold_uncertainty_score":0.1492419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02601596873141629,"score_gpt":0.2582768719646659,"score_spread":0.2322609032332496,"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."}}