{"id":"W2007586852","doi":"10.6000/1927-7229.2013.02.03.2","title":"Hepatocellular Carcinoma Microvessel Density Quantitation with Image Analysis: Correlation with Prognosis","year":2013,"lang":"en","type":"article","venue":"Journal of Analytical Oncology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hepatocellular carcinoma; Microvessel; Medicine; Correlation; Pathology; Internal medicine; Carcinoma; Gastroenterology; Immunohistochemistry; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001563947,0.0002734613,0.0002469372,0.001136514,0.00009325347,0.00038703,0.0001888284,0.0002999913,0.0007666306],"category_scores_gemma":[0.002414326,0.0001581253,0.0001501277,0.0006339345,0.0002201359,0.0004014755,0.0002558305,0.0003205555,0.0002531759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003093527,"about_ca_system_score_gemma":0.0001239432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004979031,"about_ca_topic_score_gemma":0.000556399,"domain_scores_codex":[0.999562,0.0001240959,0.00003946192,0.00009249902,0.0001384844,0.00004354453],"domain_scores_gemma":[0.9986467,0.0005138231,0.0004091444,0.0001058453,0.000247415,0.00007712586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009646838,0.0001070408,0.8565647,0.0001148652,0.0001404422,0.00007795457,0.0001217394,0.001662239,0.08467275,0.0001614432,0.0004829806,0.05492918],"study_design_scores_gemma":[0.00001955399,0.000483262,0.9525591,0.00001428899,0.00008981652,0.0007826951,0.00006566269,0.01775567,0.02712039,0.0003409036,0.0007399583,0.0000287526],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858051,0.001832873,0.01083938,0.0001071936,0.0000126996,0.00002580243,0.0001928681,0.0001845735,0.0009995011],"genre_scores_gemma":[0.9932927,0.0002564618,0.005779041,0.00002069953,0.00001400914,0.0000254057,0.0002192496,0.00001199162,0.0003804282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001563947,"threshold_uncertainty_score":0.008271039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01143955404964169,"score_gpt":0.2888982695967843,"score_spread":0.2774587155471426,"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."}}