{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001950034,0.001861572,0.001466212,0.003407992,0.001112263,0.0037618,0.003772464,0.002189918,0.2590941],"category_scores_gemma":[0.02285014,0.0006121656,0.001929798,0.003666646,0.0006276467,0.003379872,0.00265423,0.002251979,0.2422299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001321855,"about_ca_system_score_gemma":0.003212637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01000542,"about_ca_topic_score_gemma":0.0176066,"domain_scores_codex":[0.9972139,0.0004609865,0.0004273927,0.001002476,0.0005601055,0.0003350928],"domain_scores_gemma":[0.9921312,0.003173859,0.0005618765,0.001906465,0.001834421,0.000392205],"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":[0.0002144566,0.00003754973,0.002375978,0.0007377668,0.00004795466,0.00003858189,0.0000262376,0.0003129391,0.00006401566,0.001460043,0.9825191,0.01216534],"study_design_scores_gemma":[0.0002809158,0.00004953883,0.003869948,0.0005292675,0.00004601499,0.000129055,0.0001506283,0.001112107,0.000382826,0.006089746,0.9873213,0.00003881967],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005258824,0.0001832381,0.000613956,0.0003771761,0.0002146299,0.00009398867,0.9884418,0.00266108,0.006888278],"genre_scores_gemma":[0.002789074,0.0001918709,0.001996366,0.0004814868,0.00007544165,0.0003480717,0.9875472,0.0006651254,0.005905366],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2590941,"threshold_uncertainty_score":0,"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."}}