{"id":"W2147023528","doi":"10.1148/radiol.12112428","title":"Non–Small Cell Lung Cancer: Histopathologic Correlates for Texture Parameters at CT","year":2012,"lang":"en","type":"article","venue":"Radiology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":453,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Thomas Hospital","funders":"","keywords":"Medicine; Nuclear medicine; Lung cancer; Pathology; Tongue; Angiogenesis; Radiology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000387813,0.0001779313,0.0004414264,0.00007695911,0.0001173861,0.000004808259,0.0001147389,0.0001319893,0.0001298251],"category_scores_gemma":[0.0002203133,0.0001369585,0.0001471028,0.00006627723,0.0001540831,0.00002949234,0.00004491133,0.0004197326,0.00002484571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002405287,"about_ca_system_score_gemma":0.0000515202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004346104,"about_ca_topic_score_gemma":0.000002317506,"domain_scores_codex":[0.998802,0.00005514386,0.0002243037,0.0002700652,0.00006846833,0.0005800163],"domain_scores_gemma":[0.9991213,0.0002650909,0.0001166683,0.0002230871,0.00002808698,0.0002457311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001339372,0.0000945757,0.9176915,0.0002217417,0.00006300092,0.00008186918,0.0005918378,0.0002655735,0.01101553,0.0001508639,0.05779629,0.01189324],"study_design_scores_gemma":[0.01082983,0.001397032,0.2810656,0.0002776366,0.001960436,0.008837386,0.0002289852,0.191119,0.003534715,0.0003153672,0.4991668,0.001267146],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768129,0.01172506,0.005277193,0.002244595,0.001715165,0.0005304141,0.000008139094,0.00007406036,0.001612483],"genre_scores_gemma":[0.9864647,0.0004979109,0.004955969,0.003244596,0.0005466836,0.0001243514,0.00006280649,0.00003701005,0.004066018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6366259,"threshold_uncertainty_score":0.5585005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0118872542745247,"score_gpt":0.2819139874022782,"score_spread":0.2700267331277535,"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."}}