{"id":"W4244574446","doi":"10.1515/iupac.88.1258","title":"Pseudohermaphrodite","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002120187,0.0003619656,0.0005665662,0.000174059,0.0001102102,0.00003928035,0.0007766577,0.0008733852,0.00169588],"category_scores_gemma":[0.0003442395,0.0003370089,0.0001310645,0.00007346995,0.0002535495,0.00006366704,0.0001304025,0.001140959,0.00001443883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001834773,"about_ca_system_score_gemma":0.0001960995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002659355,"about_ca_topic_score_gemma":0.000287796,"domain_scores_codex":[0.9984567,0.00001365341,0.000288695,0.0002779516,0.0005337211,0.0004293042],"domain_scores_gemma":[0.9984875,0.00002688804,0.00008507074,0.001130735,0.00009712381,0.0001726504],"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":[0.00000729711,0.00002913316,6.502883e-7,0.000181931,0.00009291826,0.000191019,0.000002394338,0.000005582641,0.000001302275,0.00001146927,0.9815965,0.01787979],"study_design_scores_gemma":[0.0003554766,0.000045537,0.000007383282,0.0001871417,0.00007514195,0.00002888014,0.000005451199,0.0001036519,0.00001612992,0.0002307137,0.9985934,0.000351015],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003963308,0.003867733,0.0001685212,0.0002156108,0.001715944,0.0001320912,0.992995,0.0005192473,0.000346209],"genre_scores_gemma":[0.00003641867,0.007883722,0.00005867381,0.0001268412,0.0008208131,0.00001314292,0.9908193,0.00004372583,0.0001973498],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01752877,"threshold_uncertainty_score":0.9999082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009857618870857695,"score_gpt":0.383235325778445,"score_spread":0.3733777069075873,"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."}}