{"id":"W4235912462","doi":"10.1515/iupac.79.1432","title":"Hyper-Reflexia","year":2016,"lang":"et","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Hazard; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics; 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":[0.002893922,0.002728092,0.00191886,0.004398225,0.001127493,0.005131296,0.003955341,0.002395815,0.1328652],"category_scores_gemma":[0.02196081,0.0008914894,0.003237313,0.005950361,0.0007111975,0.003263023,0.003364527,0.002421882,0.1789594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001517043,"about_ca_system_score_gemma":0.004369251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00762751,"about_ca_topic_score_gemma":0.01865127,"domain_scores_codex":[0.9960936,0.0008520148,0.000726293,0.001324205,0.0006529594,0.0003509976],"domain_scores_gemma":[0.9932161,0.00247388,0.0006325188,0.002101829,0.001163717,0.0004118613],"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":[0.0002554508,0.00003745319,0.001230317,0.002487908,0.0001015725,0.00004043458,0.00004330594,0.0003877148,0.0001727753,0.001170943,0.9869401,0.007132052],"study_design_scores_gemma":[0.0005302068,0.00004758859,0.00214376,0.0007636248,0.00009074316,0.0001117421,0.00008910691,0.0006914851,0.0004630538,0.003731533,0.9912916,0.00004560895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001887214,0.0002117005,0.0002616457,0.0001419165,0.00006706646,0.0000588771,0.9958749,0.001709095,0.00148603],"genre_scores_gemma":[0.0006520767,0.0001706501,0.001041642,0.0002165386,0.00002962956,0.0003339948,0.996182,0.0002792558,0.001094413],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1328652,"threshold_uncertainty_score":0.4444782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01900498596338383,"score_gpt":0.4190006363880809,"score_spread":0.3999956504246971,"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."}}