{"id":"W4254364824","doi":"10.1515/iupac.79.1461","title":"Immunosuppression","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; CAS Registry Number; Toxicology; Medicine; Chemistry; Biology; Philosophy; 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":[],"consensus_categories":[],"category_scores_codex":[0.0009411004,0.001201379,0.001648415,0.002103617,0.0005204064,0.002123537,0.001536024,0.001355278,0.08230878],"category_scores_gemma":[0.008388581,0.0003580814,0.001870374,0.003246852,0.0002060958,0.001283323,0.001009702,0.001416018,0.04931818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008480214,"about_ca_system_score_gemma":0.00155619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00572096,"about_ca_topic_score_gemma":0.01415257,"domain_scores_codex":[0.9988548,0.0001868701,0.0002766015,0.0003614806,0.0001952841,0.0001249637],"domain_scores_gemma":[0.9973592,0.0008977177,0.0005235954,0.0005179538,0.0005271015,0.0001744251],"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":[0.0009473412,0.00005732141,0.008347036,0.00536364,0.0003427565,0.00009917154,0.00003040354,0.0004840258,0.0003282246,0.0007958447,0.9493496,0.03385451],"study_design_scores_gemma":[0.0008514818,0.00009578905,0.02259724,0.002789996,0.0004743279,0.0006421098,0.00006771279,0.0004273679,0.0005744028,0.002292953,0.9691275,0.00005906871],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005898515,0.00120425,0.0001702291,0.0001480657,0.00008125303,0.00005245835,0.9945747,0.0001823755,0.002996762],"genre_scores_gemma":[0.002461631,0.001000749,0.0005849574,0.0005239286,0.00006289785,0.0002592361,0.992878,0.00006230341,0.002166343],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08230878,"threshold_uncertainty_score":0.2753503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01332455795765072,"score_gpt":0.4054343178841814,"score_spread":0.3921097599265307,"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."}}