{"id":"W4240555334","doi":"10.1515/iupac.79.2176","title":"Tumorigenic","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; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009155318,0.001594848,0.002027055,0.00325068,0.001133039,0.003474512,0.002344196,0.002371849,0.09936765],"category_scores_gemma":[0.006857436,0.000626992,0.002176864,0.004553647,0.0003830876,0.001423366,0.001673484,0.002112888,0.08793807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001581384,"about_ca_system_score_gemma":0.00276929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01493424,"about_ca_topic_score_gemma":0.02889558,"domain_scores_codex":[0.9986676,0.000157772,0.000197072,0.0004588749,0.0003160679,0.0002026631],"domain_scores_gemma":[0.9977207,0.0006487454,0.0003425867,0.0006239013,0.0004955538,0.0001685778],"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":[0.0004045421,0.0000475107,0.007055057,0.003236943,0.0001917064,0.00009815834,0.00003619604,0.0005709838,0.0005055822,0.001335708,0.9745311,0.01198646],"study_design_scores_gemma":[0.0005230731,0.00005775363,0.01234684,0.001211976,0.0002894111,0.0004644493,0.00008055294,0.0004457038,0.0007619014,0.002327235,0.9814458,0.00004514936],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003722255,0.0005828898,0.00009591137,0.0001229297,0.00005738983,0.0000201691,0.9969289,0.0002045003,0.001615078],"genre_scores_gemma":[0.00108735,0.0003995822,0.0002652843,0.0002304672,0.00001952778,0.00008487823,0.9962966,0.0000557452,0.001560505],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9006324,"threshold_uncertainty_score":0.3324179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246478530806672,"score_gpt":0.386615974854533,"score_spread":0.3741511895464663,"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."}}