{"id":"W4247254238","doi":"10.1515/iupac.88.0907","title":"Hydrocephalus","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Cancer Research and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.0007664388,0.001004151,0.001549474,0.003531222,0.0006291008,0.0018171,0.001360627,0.0009416483,0.09272531],"category_scores_gemma":[0.01003115,0.0003216281,0.001445365,0.005706037,0.0003941513,0.001771754,0.001462294,0.001322189,0.03694166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009580891,"about_ca_system_score_gemma":0.002401836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007971371,"about_ca_topic_score_gemma":0.01324618,"domain_scores_codex":[0.9990189,0.0001401001,0.0003239995,0.0002665303,0.0001580875,0.00009237333],"domain_scores_gemma":[0.9967434,0.001140504,0.0007607649,0.0005693846,0.0005997376,0.0001862474],"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":[0.000474616,0.00002370817,0.007264581,0.005261936,0.0002014851,0.0003116025,0.00004857509,0.0002171827,0.000110257,0.001705901,0.9477476,0.03663255],"study_design_scores_gemma":[0.0005745098,0.00005188657,0.02279464,0.008442493,0.0002396672,0.002564878,0.0002248425,0.000310235,0.0003425513,0.007071563,0.9573065,0.00007630463],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009119488,0.002123361,0.000307011,0.0003295205,0.0001543278,0.0001082867,0.988243,0.0002882592,0.007534312],"genre_scores_gemma":[0.00543365,0.00355311,0.001178828,0.0008461529,0.0001418073,0.0003993986,0.9851864,0.000150354,0.003110299],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09272531,"threshold_uncertainty_score":0.3101971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02932051849027592,"score_gpt":0.5021367909879136,"score_spread":0.4728162724976377,"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."}}