{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005045331,0.0002270758,0.0002582624,0.0006099264,0.0001730196,0.0004313267,0.0001551073,0.0003132572,0.001155312],"category_scores_gemma":[0.002657613,0.0001612557,0.0002329739,0.0004507964,0.0002778783,0.0002862203,0.0002418797,0.0002187558,0.000267378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002375843,"about_ca_system_score_gemma":0.0001530696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008316974,"about_ca_topic_score_gemma":0.001425339,"domain_scores_codex":[0.9997388,0.00006496768,0.00002657125,0.0000563634,0.00008013788,0.00003322176],"domain_scores_gemma":[0.9983845,0.0004568918,0.0006341337,0.0001265311,0.0002452752,0.0001527141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000441815,0.00002508036,0.9920517,0.0000156565,0.00004245824,0.00006457631,0.000017255,0.0001538571,0.004566003,0.000007444645,0.00002747688,0.002586636],"study_design_scores_gemma":[0.000007635683,0.000139481,0.9978237,0.00000218586,0.00002883873,0.0004435336,0.00002970033,0.0006496774,0.0007641183,0.00001851769,0.00008977685,0.000002774001],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984626,0.000315155,0.0007336873,0.00001559567,0.000004592059,0.00001781408,0.00009783084,0.000009273491,0.0003434707],"genre_scores_gemma":[0.9995441,0.00004134889,0.0002258659,0.000006694713,0.000005870847,0.000006051342,0.00008810384,0.00000269026,0.00007919442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001155312,"threshold_uncertainty_score":0.003864944,"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."}}