{"id":"W4231689647","doi":"10.1515/iupac.87.0091","title":"Bar Test","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Civil and Structural Engineering Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Psychology; Chemistry; Linguistics; Philosophy; Data mining; Organic chemistry","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":[0.0001883653,0.0004417709,0.0004761365,0.0002165512,0.00005300233,0.00006311614,0.0004814371,0.0003430686,0.004495325],"category_scores_gemma":[0.0004617728,0.0003299111,0.0001361282,0.0001696841,0.00006771705,0.00007300369,0.0001034156,0.0006856651,0.00001283505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004117035,"about_ca_system_score_gemma":0.0001460625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002618591,"about_ca_topic_score_gemma":0.0001266656,"domain_scores_codex":[0.997929,0.00001154596,0.0003198278,0.0002963082,0.0008659001,0.0005774573],"domain_scores_gemma":[0.9987422,0.0001627886,0.00002825917,0.0006676999,0.0001737527,0.0002252864],"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":[0.000006825204,0.00001465781,0.000002605636,0.0003408978,0.0000574805,0.00006103083,0.000002517929,0.0002179231,0.00007767662,0.000002466205,0.9929091,0.006306778],"study_design_scores_gemma":[0.0003390874,0.00006974144,0.00005587524,0.0002623424,0.0000261576,0.00002141559,0.000002108888,0.0003594801,0.00005291986,0.00004908034,0.9983152,0.0004466555],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009486947,0.001155175,0.0001487941,0.0001036295,0.0009920601,0.0001472634,0.9968346,0.0003710438,0.0001525436],"genre_scores_gemma":[0.000216759,0.001832486,0.00002754635,0.00001737786,0.001148412,0.00001314,0.9962036,0.00007622648,0.0004644465],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.005860122,"threshold_uncertainty_score":0.9999153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008854654335759946,"score_gpt":0.3488409724682385,"score_spread":0.3399863181324786,"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."}}