{"id":"W4254069040","doi":"10.1515/iupac.79.2065","title":"Subfertility","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Stereochemistry Studies","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Hazard; Toxicology; Chemistry; Philosophy; Biology; Linguistics","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":[0.0002496673,0.0007615531,0.0009181538,0.00003579066,0.00019688,0.00006337975,0.0007866584,0.0007843393,0.02864624],"category_scores_gemma":[0.0009493238,0.0006018659,0.0003690924,0.00009587014,0.0003343179,0.00006205351,0.000443933,0.0007938696,0.000004357225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005904907,"about_ca_system_score_gemma":0.0005130396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004698755,"about_ca_topic_score_gemma":0.000114835,"domain_scores_codex":[0.9966496,0.00001772875,0.00067037,0.0009248595,0.001083994,0.0006534648],"domain_scores_gemma":[0.9970707,0.0001657191,0.0003339585,0.001711245,0.0004668369,0.0002515867],"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":[0.0002673181,0.0002446972,0.00003639199,0.00147066,0.0002460481,0.0001042369,0.000007591469,5.564856e-8,0.002491927,3.694536e-7,0.9937328,0.001397866],"study_design_scores_gemma":[0.0008167569,0.00001681973,0.000006544289,0.0006103222,0.0001597602,0.00002794153,0.00003867776,4.76878e-7,0.01783689,0.00009714172,0.9796967,0.0006920049],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001297237,0.001192192,0.000004760061,0.0003484834,0.0002554723,0.00005733588,0.9939443,0.0001548247,0.002745409],"genre_scores_gemma":[0.0003039524,0.0008256689,0.000006994149,0.00008116615,0.001768001,0.00002475718,0.9898901,0.00004061686,0.007058746],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02864188,"threshold_uncertainty_score":0.9996433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01567989722385612,"score_gpt":0.3814848453058906,"score_spread":0.3658049480820345,"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."}}