{"id":"W4249083840","doi":"10.1515/iupac.87.0689","title":"Tumor","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Animal testing and alternatives","field":"Veterinary","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Chemistry; Linguistics; Philosophy; Data mining; 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":[0.0009613906,0.001091421,0.001084837,0.002865816,0.0008053297,0.003097287,0.002370962,0.00179185,0.1691289],"category_scores_gemma":[0.0091152,0.0004599375,0.001576719,0.004743489,0.0003259062,0.002027918,0.001884286,0.001511163,0.1808971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001706615,"about_ca_system_score_gemma":0.002848409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01680973,"about_ca_topic_score_gemma":0.03091552,"domain_scores_codex":[0.9984576,0.0002175412,0.0002767603,0.0005141537,0.0003186157,0.0002153755],"domain_scores_gemma":[0.9966292,0.0008369395,0.0003801757,0.0008039861,0.001087835,0.0002618481],"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":[0.0001224297,0.00001517038,0.001742581,0.001078775,0.00003379315,0.0000297654,0.00002264217,0.0001721377,0.00009456143,0.001098177,0.9859409,0.009648996],"study_design_scores_gemma":[0.0001199945,0.00001588355,0.003097262,0.0006854023,0.00003347088,0.0001048897,0.00006757791,0.0002036819,0.0001984799,0.001560712,0.9938959,0.0000168198],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001707732,0.0002236544,0.0001335731,0.0002020245,0.00006448555,0.00002783606,0.9949881,0.0003219343,0.003867615],"genre_scores_gemma":[0.0006870411,0.0002242221,0.0003986254,0.0002817177,0.00002068409,0.00008772627,0.9954618,0.00008196107,0.002756326],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1691289,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09223899685494827,"score_gpt":0.5025830674601174,"score_spread":0.4103440706051691,"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."}}