{"id":"W4244100773","doi":"10.1515/iupac.88.0849","title":"Genomics","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Genetically Modified Organisms Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Data science; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005134279,0.0003326991,0.0004423875,0.00002314425,0.0004153528,0.0003193232,0.001563415,0.0004899285,0.008291104],"category_scores_gemma":[0.0005960652,0.0001248242,0.0001625757,0.00009534946,0.0002073592,0.00004508787,0.000592135,0.0006342034,0.0000292284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002154895,"about_ca_system_score_gemma":0.0002332364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006930339,"about_ca_topic_score_gemma":0.008421603,"domain_scores_codex":[0.9973689,0.00008257023,0.0002978477,0.000567469,0.001116023,0.0005671582],"domain_scores_gemma":[0.9986417,0.0001108318,0.0001817707,0.0004072405,0.0003828181,0.0002756668],"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":[0.00003760987,0.0001145185,0.000007896757,0.00001801013,0.000026299,0.00004194976,0.000001841442,5.00003e-7,0.002330326,0.00000152609,0.9749742,0.02244538],"study_design_scores_gemma":[0.00013315,0.0002865382,0.001704337,0.00003285526,0.00002976054,0.00000973917,0.00001337015,0.000002949366,0.0001336852,0.0001468357,0.9971823,0.000324544],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00768914,0.0003371627,0.000001343136,0.001302746,0.0003097564,0.0002829302,0.9899783,0.0000403187,0.00005837071],"genre_scores_gemma":[0.0002443432,0.000862394,0.00004084675,0.0001615577,0.001368235,0.000008636475,0.9968438,0.000002565784,0.0004676221],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02220809,"threshold_uncertainty_score":0.9926155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0358031053311301,"score_gpt":0.408252198870369,"score_spread":0.3724490935392389,"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."}}