{"id":"W4255920718","doi":"10.1515/iupac.88.1428","title":"Transgenic","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Science, Research, and Medicine","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; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001469231,0.0004565628,0.001116453,0.0004591135,0.0002939377,0.00007268894,0.0007921907,0.0004724264,0.005131972],"category_scores_gemma":[0.00184854,0.0003331031,0.000325181,0.0002361978,0.0007648329,0.00009265381,0.0001174328,0.001282477,0.0000155203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003629184,"about_ca_system_score_gemma":0.003851332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004214387,"about_ca_topic_score_gemma":0.001088269,"domain_scores_codex":[0.9948911,0.00005592623,0.0004833304,0.0007248711,0.003048962,0.0007958164],"domain_scores_gemma":[0.9961075,0.00007593756,0.0002168534,0.002015701,0.0007771516,0.0008069176],"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":[0.0004533589,0.0003158972,0.00004414569,0.0005094918,0.0001286004,0.0005766478,0.00003471482,1.190049e-7,0.00006225486,0.000001608607,0.9895428,0.008330348],"study_design_scores_gemma":[0.003266543,0.001025325,0.0007086353,0.001006438,0.0004488984,0.0001674854,0.00006861436,0.000007317621,0.00006176884,0.00002586667,0.9929078,0.0003052941],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008406006,0.002221488,0.00003678622,0.002670753,0.001135501,0.0006778209,0.9918431,0.00006609826,0.0005078726],"genre_scores_gemma":[0.0001794849,0.004603832,0.00005350464,0.0009216376,0.002416779,0.00001921029,0.9871112,0.00004075503,0.004653614],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008025054,"threshold_uncertainty_score":0.9999121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04374285981676207,"score_gpt":0.520749604046805,"score_spread":0.477006744230043,"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."}}