{"id":"W4242005492","doi":"10.1515/iupac.79.1875","title":"Pyrexia","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Hematological disorders and diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; 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":[0.001161733,0.0009905697,0.001165297,0.002538441,0.0005868591,0.003535038,0.00121815,0.0009308317,0.3409111],"category_scores_gemma":[0.01358098,0.0003807868,0.001215439,0.004800199,0.000315298,0.001616401,0.001596975,0.001425865,0.2980172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00119921,"about_ca_system_score_gemma":0.002328597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007271763,"about_ca_topic_score_gemma":0.01102739,"domain_scores_codex":[0.9982298,0.0003460602,0.0003305728,0.0005862548,0.0003598001,0.0001474514],"domain_scores_gemma":[0.9962472,0.00126906,0.000533551,0.000726386,0.0009291327,0.0002946666],"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":[0.0001177569,0.00001143379,0.001248514,0.0008203307,0.00003545287,0.00003416477,0.00001583189,0.000103916,0.00005111269,0.0009068273,0.9824289,0.01422569],"study_design_scores_gemma":[0.00007169093,0.00001083005,0.002426296,0.0004661836,0.00002325015,0.0001000195,0.00003163591,0.00007557693,0.00006960137,0.0008662121,0.9958487,0.00001014577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003751144,0.001114384,0.0002795489,0.0006019023,0.000344014,0.00004813376,0.9811967,0.0006415698,0.01539851],"genre_scores_gemma":[0.002323484,0.001587381,0.0006848251,0.001211904,0.000216615,0.0002231861,0.9756829,0.0003914461,0.01767824],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3409111,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02040806312874699,"score_gpt":0.4315368458564847,"score_spread":0.4111287827277377,"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."}}