{"id":"W2891130282","doi":"10.23889/ijpds.v3i4.948","title":"BC Data ScoutTM: A New Tool To Investigate Datasets For Health Research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Ministry of Health","funders":"","keywords":"Computer science; Data quality; Data science; Sophistication; Benchmarking; Population; Service (business); World Wide Web; Database; Medicine; Business","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":[],"consensus_categories":[],"category_scores_codex":[0.05073285,0.001871165,0.001745725,0.01311266,0.002250484,0.008057108,0.004433462,0.002674312,0.1018538],"category_scores_gemma":[0.1642679,0.002430613,0.002563182,0.01535669,0.001382755,0.01091663,0.01273503,0.00453306,0.02531196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003540526,"about_ca_system_score_gemma":0.01298439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01042922,"about_ca_topic_score_gemma":0.02144853,"domain_scores_codex":[0.9785773,0.009254619,0.004523479,0.002295233,0.004634173,0.0007153522],"domain_scores_gemma":[0.8099278,0.1368081,0.008267858,0.02152835,0.01480191,0.008666079],"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":[0.000695621,0.0001394228,0.004841825,0.005037664,0.0002928817,0.0002729432,0.002616738,0.0008690106,0.001680063,0.0218485,0.8134058,0.1482996],"study_design_scores_gemma":[0.0003786721,0.00007021952,0.003017844,0.001569931,0.00007906657,0.0001863943,0.0005033838,0.003207267,0.001300456,0.01730843,0.9722167,0.0001617382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.004903747,0.002451201,0.2326584,0.01344855,0.001722673,0.007604197,0.5019491,0.2022475,0.03301457],"genre_scores_gemma":[0.01854056,0.00182778,0.7073264,0.004414414,0.0004625751,0.01702995,0.2029748,0.03855215,0.008871424],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1018538,"threshold_uncertainty_score":0.3407348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4359980006695067,"score_gpt":0.5798542166762604,"score_spread":0.1438562160067537,"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."}}