{"id":"W4249357864","doi":"10.1515/iupac.88.0604","title":"Chromosome","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Carcinogens and Genotoxicity Assessment","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001187255,0.00140809,0.001182151,0.00316584,0.0009831575,0.003240746,0.002329001,0.001701846,0.2421681],"category_scores_gemma":[0.01123717,0.000612198,0.001392075,0.005567867,0.0003993733,0.002562603,0.002328817,0.001567103,0.2509247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001419652,"about_ca_system_score_gemma":0.002792958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01477687,"about_ca_topic_score_gemma":0.02528415,"domain_scores_codex":[0.9982517,0.0002560774,0.0003110774,0.0006382802,0.00036349,0.0001792104],"domain_scores_gemma":[0.9960253,0.001097497,0.0003912384,0.001031875,0.0012251,0.0002289304],"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":[0.00008787524,0.00001221037,0.001162594,0.0009457273,0.00002959112,0.00002283948,0.00002927489,0.0001255439,0.0001260434,0.001241182,0.9866503,0.009566873],"study_design_scores_gemma":[0.00006769478,0.000009228355,0.00214683,0.0004034366,0.00001838927,0.00004826062,0.00004834787,0.00008722516,0.0001534793,0.001320678,0.9956813,0.00001524581],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001074026,0.0001260554,0.0001798029,0.0001257824,0.0000501473,0.00002423747,0.9958766,0.0003876527,0.003122229],"genre_scores_gemma":[0.0003848949,0.0001573232,0.0004925863,0.0002072098,0.00001453658,0.0001079893,0.9960991,0.0001234667,0.002412929],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2421681,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01354112427152251,"score_gpt":0.4138529009124589,"score_spread":0.4003117766409364,"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."}}