{"id":"W2120254749","doi":"10.3174/ajnr.a4110","title":"MRI Texture Analysis Predicts p53 Status in Head and Neck Squamous Cell Carcinoma","year":2014,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Medicine; Head and neck squamous-cell carcinoma; Radiology; Head and neck cancer; Carcinoma; Pathology; Oncology; Cancer; Internal medicine","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":[0.0004584848,0.0003444623,0.0002973112,0.001205831,0.0001601469,0.0004407434,0.0001547306,0.0003178544,0.0009669897],"category_scores_gemma":[0.003039268,0.0001250144,0.0003038082,0.0003470711,0.0001981642,0.0002315106,0.0002023358,0.0001807249,0.0002657221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002195191,"about_ca_system_score_gemma":0.0001569309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002044149,"about_ca_topic_score_gemma":0.002563948,"domain_scores_codex":[0.999866,0.00002825932,0.00001417411,0.00002083914,0.00005009889,0.00002061796],"domain_scores_gemma":[0.9992045,0.0002836333,0.0002067996,0.00005329674,0.0001868435,0.00006501995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004806484,0.00005653406,0.9683935,0.00002936559,0.00006330029,0.0002164227,0.00004278238,0.002114387,0.009793857,0.00001831877,0.0002085736,0.01858222],"study_design_scores_gemma":[0.00001164435,0.000213768,0.9727432,0.00001308691,0.00007133748,0.0008934282,0.0001212496,0.02263585,0.002942329,0.0001275832,0.0002167873,0.000009676774],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985065,0.0001854355,0.0009028774,0.00003110242,0.000005717729,0.00001144251,0.00009041708,0.00001725698,0.0002492135],"genre_scores_gemma":[0.9994036,0.00005542005,0.0003937525,0.000005611165,0.000004361765,0.000003720795,0.00007631478,0.0000024647,0.0000547061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002044149,"threshold_uncertainty_score":0.0040645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00577654971546891,"score_gpt":0.2612694031756125,"score_spread":0.2554928534601436,"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."}}