{"id":"W4238644450","doi":"10.1515/iupac.88.1065","title":"Midgut","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); 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":[0.001935612,0.001267699,0.001412338,0.004795408,0.001010709,0.004872703,0.002296552,0.001989335,0.2416341],"category_scores_gemma":[0.01959836,0.0007167633,0.001500421,0.008209817,0.0004421068,0.003159022,0.002967955,0.001918508,0.2765404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001880784,"about_ca_system_score_gemma":0.004012215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0143868,"about_ca_topic_score_gemma":0.02344832,"domain_scores_codex":[0.997534,0.0005039629,0.0005432601,0.0005829825,0.000529068,0.00030675],"domain_scores_gemma":[0.9924358,0.00222573,0.0009299954,0.001413611,0.002535311,0.0004595004],"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":[0.00009186564,0.000009194158,0.0007527276,0.001264199,0.00002253249,0.00001570612,0.00002794869,0.00007038029,0.00005324874,0.0009070506,0.9920768,0.004708421],"study_design_scores_gemma":[0.0001339324,0.00001217684,0.002185356,0.001261184,0.00002193726,0.00004875229,0.00007744695,0.00008893177,0.0001125875,0.001190269,0.9948486,0.00001876756],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008123434,0.0001210428,0.0000683018,0.0001726905,0.00004996652,0.0000232086,0.9970293,0.0002450911,0.002209028],"genre_scores_gemma":[0.0003460553,0.0002075447,0.0002808591,0.0002557915,0.00002601004,0.0001518452,0.9963368,0.0001359049,0.002259121],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2416341,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02593450415429583,"score_gpt":0.4741501283787261,"score_spread":0.4482156242244302,"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."}}