{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002679933,0.0003812929,0.0007983852,0.0002106316,0.0001961149,0.0000862123,0.0003118126,0.0002782827,0.004814704],"category_scores_gemma":[0.0005524638,0.0002959313,0.0002705514,0.00007343273,0.0001957647,0.00005114802,0.0001761518,0.0006994973,0.00002167028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009883491,"about_ca_system_score_gemma":0.002831748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001101334,"about_ca_topic_score_gemma":0.002461482,"domain_scores_codex":[0.9970878,0.00002732391,0.0002809808,0.0005014843,0.001586799,0.0005155748],"domain_scores_gemma":[0.997324,0.00003160724,0.0001801689,0.001585966,0.0003926519,0.0004855288],"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":[0.000853519,0.0005614944,0.0000288448,0.00035881,0.0004205031,0.002219095,0.000004636663,1.642047e-7,0.000002401091,8.161342e-7,0.9879059,0.007643883],"study_design_scores_gemma":[0.00338766,0.001104061,0.0001878695,0.0005965942,0.0004351318,0.0001963495,0.000006745431,0.000003546197,0.00002165752,0.00004089621,0.9937863,0.0002331768],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001355532,0.003774514,0.000004264857,0.001521803,0.0003735723,0.0005943135,0.9932055,0.00004991813,0.0003405746],"genre_scores_gemma":[0.00009004209,0.003345351,0.00003087039,0.0002586411,0.001313679,0.00004000376,0.9920899,0.00003964342,0.002791873],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007410706,"threshold_uncertainty_score":0.9999493,"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."}}