{"id":"W4230486506","doi":"10.1515/iupac.88.0958","title":"Inversion, Chromosomal","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009429035,0.001076266,0.001052321,0.003751502,0.0010811,0.00351625,0.001677546,0.001143964,0.301725],"category_scores_gemma":[0.01740474,0.0004055392,0.001046062,0.009050871,0.0005225609,0.003129772,0.002187932,0.001542049,0.2000962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040289,"about_ca_system_score_gemma":0.002592563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01539862,"about_ca_topic_score_gemma":0.01978232,"domain_scores_codex":[0.9983463,0.0002348201,0.0003459577,0.000522009,0.0003706586,0.0001802567],"domain_scores_gemma":[0.9953052,0.001529023,0.0005620811,0.001148998,0.001212751,0.0002420533],"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":[0.00007224359,0.000007766734,0.001840377,0.000946323,0.00002254594,0.00004054969,0.00004006275,0.00008848568,0.00005596524,0.001736002,0.9760411,0.01910859],"study_design_scores_gemma":[0.00004161842,0.000006255866,0.002886205,0.0004957863,0.00001825068,0.0001076017,0.00008459428,0.00005182164,0.00005472193,0.00229735,0.9939434,0.00001238254],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003008005,0.0006129914,0.0004096855,0.0004348095,0.0002285461,0.00004659381,0.983528,0.0004753727,0.01396315],"genre_scores_gemma":[0.002218466,0.001175161,0.001104976,0.0008004178,0.00009725823,0.0002306536,0.9836661,0.0003288704,0.01037818],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.301725,"threshold_uncertainty_score":0.9960046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01106725216909081,"score_gpt":0.4352562585384168,"score_spread":0.4241890063693259,"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."}}