{"id":"W6931106457","doi":"10.5281/zenodo.3597933","title":"DDIEM - Drug Database for inborn errors of metabolism","year":2020,"lang":"en","type":"other","venue":"Figshare","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Mechanism (biology); Categorization; Drug; Inborn error of metabolism; Ontology; Drug metabolism; MEDLINE; Computer database","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":[0.001834606,0.001302873,0.00124476,0.006899616,0.0007931768,0.003113728,0.002509145,0.002512581,0.1395298],"category_scores_gemma":[0.006595802,0.000621833,0.001291849,0.007282221,0.0004142119,0.003129232,0.002900405,0.001632927,0.08228811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001993366,"about_ca_system_score_gemma":0.003178958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005219222,"about_ca_topic_score_gemma":0.006596709,"domain_scores_codex":[0.9990553,0.0001694763,0.0001663477,0.000161534,0.0003579102,0.00008935867],"domain_scores_gemma":[0.9971143,0.001103379,0.0004115269,0.0004265208,0.0005620422,0.0003823217],"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":[0.0004156496,0.00005917567,0.00116064,0.003323189,0.00008967194,0.0003307975,0.00009822347,0.0009612687,0.001156845,0.02513713,0.9072258,0.06004162],"study_design_scores_gemma":[0.00005964571,0.00001178395,0.0005002984,0.0002733134,0.00002769269,0.0001576219,0.00001824062,0.0002906622,0.0005807001,0.005044012,0.9930167,0.00001942244],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008590558,0.003440363,0.01147022,0.001929743,0.0003521747,0.0002163204,0.909361,0.01635759,0.05601341],"genre_scores_gemma":[0.006700183,0.005546752,0.02230339,0.002467055,0.0001475237,0.0003159534,0.9409814,0.00453099,0.01700675],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1395298,"threshold_uncertainty_score":0.4667737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05368914317224467,"score_gpt":0.3255251400929409,"score_spread":0.2718359969206963,"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."}}