{"id":"W4230963775","doi":"10.1515/iupac.88.1003","title":"Lysosomal Storage Disease","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Lysosomal Storage Disorders Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Data science; Linguistics; Data mining; Philosophy","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":[0.001459397,0.00111529,0.001876483,0.005370655,0.0006226285,0.002349175,0.001679373,0.001504555,0.07075254],"category_scores_gemma":[0.01496181,0.00046787,0.001657753,0.009744678,0.0003204284,0.001684514,0.002045496,0.001603491,0.03595845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001376774,"about_ca_system_score_gemma":0.003283631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01100019,"about_ca_topic_score_gemma":0.02233292,"domain_scores_codex":[0.9981371,0.0002911041,0.0006898319,0.0004479047,0.000273818,0.0001601824],"domain_scores_gemma":[0.9942577,0.001809231,0.001243404,0.0009377171,0.001388891,0.0003630501],"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":[0.0002480671,0.0000186583,0.004108957,0.006274631,0.0001861521,0.00008505523,0.00004961176,0.0001948551,0.0001554517,0.001292481,0.9738278,0.01355841],"study_design_scores_gemma":[0.000453297,0.00003568114,0.02072031,0.006271283,0.0002469521,0.0004942272,0.0001320621,0.0002257635,0.0002756595,0.002656842,0.9684241,0.00006377798],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002152797,0.0006726725,0.00009563134,0.0001504874,0.00004279073,0.00003945527,0.9972883,0.00008325029,0.001412112],"genre_scores_gemma":[0.0009562932,0.0009063967,0.0005145153,0.0002467094,0.00002984829,0.0003152273,0.9960663,0.00004022184,0.0009245418],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07075254,"threshold_uncertainty_score":0.2366908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02736297134066258,"score_gpt":0.449585892607532,"score_spread":0.4222229212668694,"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."}}