{"id":"W4247724526","doi":"10.1515/iupac.76.0129","title":"Autooxidation","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Relation (database); Toxicology; Computer science; Medicine; Pharmacology; Philosophy; Biology; Data mining; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001246745,0.002023224,0.001367629,0.004817539,0.0008885218,0.003105865,0.00206436,0.001395264,0.1024207],"category_scores_gemma":[0.006804421,0.0007145688,0.001802199,0.006924252,0.0003793509,0.002331306,0.002194278,0.001727687,0.1284989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001486184,"about_ca_system_score_gemma":0.002592667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01413757,"about_ca_topic_score_gemma":0.02672424,"domain_scores_codex":[0.998274,0.000251602,0.0003388553,0.0005862835,0.0004064089,0.0001429086],"domain_scores_gemma":[0.9973558,0.0007514534,0.0003777751,0.0006673511,0.0007079467,0.0001397559],"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":[0.0001244152,0.00002774511,0.001416673,0.003006767,0.00005389872,0.00003285926,0.00004971301,0.0002805852,0.000409625,0.001117427,0.9835165,0.009963746],"study_design_scores_gemma":[0.00007699319,0.00001418017,0.003238956,0.0006132798,0.00003365505,0.00004822777,0.00005428955,0.0001519265,0.0003637616,0.001121841,0.9942579,0.00002493272],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001364859,0.0002091533,0.0001135969,0.00004292843,0.00002461369,0.00001699889,0.9979067,0.0003419488,0.001207667],"genre_scores_gemma":[0.0002642949,0.0001848458,0.0003565235,0.00005725955,0.000006311403,0.00007708406,0.9979989,0.00009508649,0.0009596868],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8975793,"threshold_uncertainty_score":0.3426312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005516685546787024,"score_gpt":0.3252559385072824,"score_spread":0.3197392529604954,"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."}}