{"id":"W4236724413","doi":"10.1515/iupac.88.1133","title":"Offspring","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Psychology; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001333748,0.001148353,0.001150469,0.002580408,0.0008882682,0.002699258,0.002106516,0.001461374,0.2256356],"category_scores_gemma":[0.01223597,0.0005835253,0.001422494,0.00513955,0.0002911979,0.002174786,0.002274823,0.001595511,0.1647108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001401572,"about_ca_system_score_gemma":0.002410752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01699438,"about_ca_topic_score_gemma":0.02478792,"domain_scores_codex":[0.9983534,0.0002474837,0.0003503981,0.0005091778,0.0003686631,0.0001709716],"domain_scores_gemma":[0.9954397,0.001279631,0.0006264268,0.001022067,0.001397986,0.0002341793],"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":[0.000144675,0.00001662682,0.002306894,0.001429894,0.00004240691,0.00003586782,0.0000355891,0.0001271108,0.0000688174,0.00143956,0.9806508,0.01370184],"study_design_scores_gemma":[0.0001350857,0.00001625204,0.005633986,0.0008958926,0.00003786513,0.0001027837,0.00008772647,0.00008375925,0.0001273887,0.001707956,0.99115,0.00002143038],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001812863,0.000169918,0.0001331536,0.0001498509,0.00005514979,0.00003152372,0.9953423,0.0001842555,0.003752552],"genre_scores_gemma":[0.0008064699,0.0003281455,0.0004478899,0.0003280422,0.00002590654,0.0001730751,0.9936092,0.00009422151,0.004187036],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7743644,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02601752590722972,"score_gpt":0.4560401331773769,"score_spread":0.4300226072701472,"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."}}