{"id":"W2149620854","doi":"10.1126/scitranslmed.3006260","title":"Differential Diagnosis of Azoospermia with Proteomic Biomarkers ECM1 and TEX101 Quantified in Seminal Plasma","year":2013,"lang":"en","type":"article","venue":"Science Translational Medicine","topic":"Urologic and reproductive health conditions","field":"Medicine","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; Mount Sinai Hospital; Lunenfeld-Tanenbaum Research Institute","funders":"Canadian Institutes of Health Research","keywords":"Azoospermia; Differential diagnosis; Differential (mechanical device); Medicine; Andrology; Biology; Pathology; Infertility; Physics; Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003248203,0.0001103693,0.0002545535,0.0003401273,0.0001077657,0.000004787495,0.00007507938,0.00003926594,0.0007146045],"category_scores_gemma":[0.000137739,0.00006631984,0.00001683463,0.0006298706,0.002394407,0.0001662218,0.000008849573,0.0001437379,0.00000533914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002328709,"about_ca_system_score_gemma":0.0002706304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002699276,"about_ca_topic_score_gemma":0.00002845564,"domain_scores_codex":[0.9985712,0.00002484569,0.0002984153,0.00036864,0.0005079478,0.0002289219],"domain_scores_gemma":[0.999321,0.0001226681,0.00007716972,0.0001428026,0.0001776557,0.0001587331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003464772,0.0002047538,0.9022363,0.0001468113,0.00002769311,0.000009060786,0.001179674,0.00001178352,0.08751055,0.001293572,0.0001250502,0.00690832],"study_design_scores_gemma":[0.002041867,0.0006352172,0.9906583,0.0002472207,0.00004214386,0.00006505958,0.0002686137,0.001184935,0.004072203,0.0006821395,0.00002807206,0.00007426232],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789584,0.0001164296,0.0002415077,0.01881682,0.00008337464,0.0009337108,0.000006141531,0.00001373026,0.000829923],"genre_scores_gemma":[0.9982648,0.00004080774,0.001324027,0.00009913746,0.00007478839,0.0001196417,0.00001366195,0.000005528867,0.00005756412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08842201,"threshold_uncertainty_score":0.8822293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02296457492684563,"score_gpt":0.2961896171363544,"score_spread":0.2732250422095088,"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."}}