{"id":"W2442688388","doi":"10.1097/bot.0000000000000463","title":"Bigger Data, Bigger Problems","year":2015,"lang":"en","type":"article","venue":"Journal of Orthopaedic Trauma","topic":"Hip and Femur Fractures","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Medicine; Merge (version control); Big data; Health care; Data quality; Certainty; Data science; MEDLINE; Actuarial science; Data mining; Operations management; Information retrieval; Computer science; Metric (unit)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001246445,0.000166722,0.0004533528,0.0002759877,0.00003732754,0.00003125322,0.0003083821,0.0001277952,0.0002593855],"category_scores_gemma":[0.0004119252,0.0001091636,0.0001828488,0.0002519255,0.00008803663,0.000345088,0.0000583073,0.0005778591,0.00008831579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005214967,"about_ca_system_score_gemma":0.0004238646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001769772,"about_ca_topic_score_gemma":0.0000116654,"domain_scores_codex":[0.99798,0.00005648411,0.0006782725,0.0001826386,0.0008302193,0.0002723816],"domain_scores_gemma":[0.9980304,0.00005582616,0.0003795217,0.0005119469,0.0003856012,0.0006366954],"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":[0.001296541,0.001227967,0.2202506,0.0002228981,0.00065584,0.002089489,0.002654513,0.00009453172,0.001445667,0.00008659608,0.4758096,0.2941658],"study_design_scores_gemma":[0.007486077,0.001429742,0.1083112,0.000348671,0.0004303317,0.004100722,0.0004855839,0.0001580332,0.0004478696,0.0002057829,0.8763688,0.0002272226],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9700391,0.005536919,0.001567238,0.006065044,0.001899068,0.0002777382,0.00002245725,0.00005513442,0.01453724],"genre_scores_gemma":[0.9927667,0.0001489234,0.002588497,0.001067488,0.002099832,0.000001344532,0.00002193551,0.00003281035,0.001272453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4005592,"threshold_uncertainty_score":0.4451562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1134273422780063,"score_gpt":0.3324847487840265,"score_spread":0.2190574065060202,"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."}}