{"id":"W4241605948","doi":"10.1515/iupac.88.1358","title":"Spermiogenesis","year":2017,"lang":"fi","type":"dataset","venue":"IUPAC Standards Online","topic":"Sperm and Testicular Function","field":"Medicine","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; Data mining; Philosophy","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":[0.001094764,0.001089938,0.001798259,0.0004480689,0.0006999257,0.0002456699,0.0007505746,0.001155769,0.02156112],"category_scores_gemma":[0.00534332,0.0009687119,0.0006957896,0.0002444155,0.0005151636,0.0001777857,0.000339176,0.001162475,0.0001959787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009971175,"about_ca_system_score_gemma":0.002733331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007206094,"about_ca_topic_score_gemma":0.0008859318,"domain_scores_codex":[0.9941894,0.0001519448,0.0009579369,0.001273369,0.002412559,0.001014744],"domain_scores_gemma":[0.9935777,0.0001815397,0.0008130533,0.003325572,0.001360177,0.0007419189],"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":[0.0008264104,0.001063266,0.001583554,0.0008280767,0.0007728206,0.001993431,0.00002735168,0.000002959378,0.000110005,0.00001291852,0.9711661,0.02161305],"study_design_scores_gemma":[0.003766541,0.001287963,0.007110682,0.002170553,0.003513849,0.0004746723,0.00008438856,0.00009270868,0.0001142693,0.00004729206,0.9804188,0.0009182995],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004219976,0.007987033,0.0001506372,0.001244005,0.005779709,0.0008637199,0.9789265,0.00013475,0.00069368],"genre_scores_gemma":[0.001272115,0.005004672,0.0001275641,0.0006643533,0.008590572,0.00002287782,0.9767364,0.0001569082,0.007424496],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02136514,"threshold_uncertainty_score":0.9992763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02574354089510219,"score_gpt":0.4208357687184245,"score_spread":0.3950922278233224,"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."}}