{"id":"W4236052947","doi":"10.1515/iupac.79.2084","title":"Symptomatology","year":2016,"lang":"en","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; Computer science; Toxicology; Library science; Chemistry; Philosophy; Biology; Linguistics","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":[0.0001469632,0.0005241291,0.0006772248,0.00006850306,0.0001456412,0.00002134441,0.0007452308,0.0007466778,0.06554505],"category_scores_gemma":[0.0003796573,0.0004400529,0.0001877109,0.00006613199,0.0002913208,0.00006577939,0.0002102208,0.0006585685,0.00001157068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007324201,"about_ca_system_score_gemma":0.0005976959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007573498,"about_ca_topic_score_gemma":0.00003458194,"domain_scores_codex":[0.9974986,0.00001841354,0.0005332704,0.0006750036,0.0007503054,0.0005243576],"domain_scores_gemma":[0.9978752,0.0001085609,0.0003526885,0.001264519,0.0002050369,0.0001940675],"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":[0.00006239555,0.0001884251,0.000008476579,0.0007011539,0.0001235114,0.0001317616,0.000003770407,2.8301e-7,0.0009540722,0.000005695313,0.9961182,0.001702239],"study_design_scores_gemma":[0.0008188256,0.00001878179,1.358767e-7,0.0005973086,0.00009402774,0.00006628629,0.0000118701,3.829983e-7,0.003133772,0.0001056917,0.9946208,0.0005321349],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001414511,0.00073491,0.00002748029,0.0001220765,0.0007395164,0.00004342153,0.995786,0.0001357421,0.00226941],"genre_scores_gemma":[0.00001197252,0.0006678779,0.0000357967,0.0001788801,0.001301837,0.00002116888,0.9894515,0.00005016706,0.008280762],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06553348,"threshold_uncertainty_score":0.9998052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048703254701081,"score_gpt":0.3857555333639782,"score_spread":0.3752685008169674,"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."}}