{"id":"W1996400688","doi":"10.1371/journal.pone.0027620","title":"Crowd Intelligence for the Classification of Fractures and Beyond","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Radiology practices and education","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Orthopaedic Trauma Association","keywords":"Displacement (psychology); Medical diagnosis; Reliability (semiconductor); Medicine; Kappa; Digital radiography; Inter-rater reliability; The Internet; Computer science; Radiography; Medical physics; Statistics; Surgery; Psychology; Mathematics; Pathology; World Wide Web","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":[0.0001297283,0.00002709273,0.00006784188,0.00001707878,0.00003210932,0.000002315632,0.00003007021,0.00003274034,0.00007217481],"category_scores_gemma":[0.0002508336,0.00001703715,0.00001084011,0.00002641882,0.00006059821,0.0000419501,0.000004114286,0.00004993749,0.000003034572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004390995,"about_ca_system_score_gemma":0.00001679447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001670762,"about_ca_topic_score_gemma":0.000002801604,"domain_scores_codex":[0.9997605,0.000008609701,0.00008144666,0.00006189744,0.00004347138,0.0000440934],"domain_scores_gemma":[0.999532,0.0002049809,0.00006666012,0.0001155275,0.00006251324,0.00001827018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002323183,0.006944232,0.2666763,0.001087248,0.001828344,0.000001310243,0.0364597,0.000001541254,0.4697299,0.03088983,0.004770359,0.179288],"study_design_scores_gemma":[0.0001557701,0.0003803504,0.8710139,0.00004361684,0.0005474939,0.000005178812,0.001708066,0.001164121,0.1213829,0.002802338,0.0007505663,0.00004567028],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991695,0.0008127237,0.00124327,0.003515214,0.00003636444,0.0002737016,0.00000142844,0.000006555672,0.002415667],"genre_scores_gemma":[0.9939313,0.0003555531,0.005163927,0.0002429935,0.0000696194,0.00002610862,0.000003874112,0.00000343512,0.0002031835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6043376,"threshold_uncertainty_score":0.07902636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2108245840256976,"score_gpt":0.3412122828708147,"score_spread":0.1303876988451172,"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."}}