{"id":"W1530069278","doi":"10.1111/bpa.12171","title":"<scp>I</scp>nternational <scp>S</scp>ociety of <scp>N</scp>europathology‐<scp>H</scp>aarlem <scp>C</scp>onsensus <scp>G</scp>uidelines for <scp>N</scp>ervous <scp>S</scp>ystem <scp>T</scp>umor <scp>C</scp>lassification and <scp>G</scp>rading","year":2014,"lang":"en","type":"article","venue":"Brain Pathology","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":572,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; University of Toronto; Hospital for Sick Children; Princess Margaret Cancer Centre","funders":"World Health Organization","keywords":"Neuropathology; Medical diagnosis; Medicine; Set (abstract data type); Bioinformatics; Neuroscience; Computational biology; Computer science; Pathology; Biology; Disease","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":["metaresearch","metaepi_narrow","metaepi_broad","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","research_integrity"],"category_scores_codex":[0.01887528,0.01494412,0.01807143,0.01073646,0.006604684,0.003597462,0.01099381,0.01213135,0.00006958233],"category_scores_gemma":[0.2296122,0.01541923,0.008863827,0.01103731,0.008125981,0.004745922,0.006344041,0.01136185,0.003934516],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004366866,"about_ca_system_score_gemma":0.004628706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008649958,"about_ca_topic_score_gemma":0.0009668112,"domain_scores_codex":[0.9234581,0.009857168,0.01800284,0.01835003,0.01102738,0.01930448],"domain_scores_gemma":[0.7989494,0.1536342,0.01630639,0.01248015,0.009527038,0.009102874],"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":[0.00008649175,0.0127693,0.08024208,0.006270461,0.007762442,0.01030107,0.03848436,0.002449965,0.1045688,0.01018935,0.7227698,0.004105919],"study_design_scores_gemma":[0.03771545,0.009004861,0.07819444,0.00383266,0.008519654,0.01841244,0.08000717,0.01132703,0.06104413,0.006160929,0.6847473,0.001033954],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8833688,0.03013518,0.007943535,0.001658325,0.01299481,0.01802019,0.008923541,0.005502827,0.03145277],"genre_scores_gemma":[0.7996307,0.01435384,0.02358418,0.01347139,0.01661149,0.01289376,0.01578602,0.007032345,0.0966363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2107369,"threshold_uncertainty_score":0.9994552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02781940748550444,"score_gpt":0.2799538387606934,"score_spread":0.252134431275189,"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."}}