{"id":"W4392133077","doi":"10.1007/s00234-024-03319-w","title":"Whole-tumor histogram analysis of postcontrast T1-weighted and apparent diffusion coefficient in predicting the grade and proliferative activity of adult intracranial ependymomas","year":2024,"lang":"en","type":"article","venue":"Neuroradiology","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Science and Technology Program of Gansu Province; National Natural Science Foundation of China","keywords":"Medicine; Effective diffusion coefficient; Nuclear medicine; Kurtosis; Histogram; Receiver operating characteristic; Coefficient of variation; Skewness; Percentile; Standard deviation; Correlation coefficient; Radiology; Internal medicine; Statistics; Mathematics; Magnetic resonance imaging; Artificial intelligence","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":[0.0005468576,0.0002547986,0.0001498744,0.0008651871,0.0001199113,0.0004085852,0.0002043576,0.0002335519,0.0003727752],"category_scores_gemma":[0.001854081,0.0001145923,0.0001250701,0.000280817,0.0001770825,0.0004912927,0.0001464845,0.0002175898,0.0001053092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000141749,"about_ca_system_score_gemma":0.000158846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002166342,"about_ca_topic_score_gemma":0.003354883,"domain_scores_codex":[0.9999183,0.00002355877,0.00001199298,0.00001436509,0.00001791315,0.00001377763],"domain_scores_gemma":[0.9993948,0.0002736288,0.00008418925,0.00002762004,0.0001116833,0.0001081022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004326292,0.0001727892,0.9364367,0.00004280292,0.0001294751,0.0005584385,0.0001170518,0.00099915,0.01815823,0.00007317888,0.0002216825,0.03876422],"study_design_scores_gemma":[0.00002568004,0.0005750055,0.9817037,0.000008948333,0.0001031799,0.001388075,0.0001738883,0.009712721,0.005901233,0.0001098805,0.0002826712,0.00001508112],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991086,0.0002345294,0.0003202188,0.00001310767,0.00000435314,0.000003660153,0.00003262978,0.00001030005,0.0002724536],"genre_scores_gemma":[0.9995772,0.00007600938,0.0002164354,0.000004399565,0.000003133302,0.000001190381,0.00003319074,0.000002064106,0.00008644581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002166342,"threshold_uncertainty_score":0.004307449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006025249301578,"score_gpt":0.2622572551530349,"score_spread":0.2521970026600192,"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."}}