{"id":"W4248864887","doi":"10.1515/iupac.87.0404","title":"Myelogram","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Biomedical and Chemical Research","field":"Medicine","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":[0.0005902664,0.001136852,0.001331395,0.00288656,0.0004789403,0.001557278,0.001230134,0.001086937,0.1389565],"category_scores_gemma":[0.01055815,0.0003204375,0.001244476,0.002965567,0.0002365658,0.001493152,0.001067336,0.00125116,0.06005499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009682572,"about_ca_system_score_gemma":0.00187137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007041052,"about_ca_topic_score_gemma":0.01234276,"domain_scores_codex":[0.9992893,0.00009316672,0.0002142041,0.0002205497,0.0001092587,0.00007354114],"domain_scores_gemma":[0.9960468,0.001256168,0.0006626586,0.0006700084,0.001150173,0.0002140312],"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":[0.001338423,0.00004434284,0.01419924,0.003848572,0.000199687,0.0004102175,0.00003840922,0.0006447614,0.0002252268,0.001075687,0.9094294,0.06854613],"study_design_scores_gemma":[0.0006722058,0.0001310853,0.04126991,0.004332871,0.0002890483,0.002629854,0.0001583855,0.0007618894,0.0008829189,0.005805372,0.9429662,0.0001002735],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001594531,0.001782238,0.0004830006,0.0004125232,0.0001203715,0.0001732215,0.9825761,0.0005888331,0.01226916],"genre_scores_gemma":[0.0120728,0.002955106,0.002310325,0.001005577,0.0001815562,0.0006027057,0.9727039,0.0002465146,0.007921499],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1389565,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02293639472639461,"score_gpt":0.4716880137002118,"score_spread":0.4487516189738172,"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."}}