{"id":"W4411291698","doi":"10.1158/1557-3265.sabcs24-p2-09-01","title":"Abstract P2-09-01: Preliminary Findings from the Breast Cancer Combined Visualization And Characterization Tools (bCOMBAT): Low-Dose PEM and Liquid Biopsy Study","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Breast cancer; Cancer; Biopsy; Visualization; Liquid biopsy; Radiology; Pathology; Internal medicine; Computer science; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003136136,0.0005354855,0.0003538843,0.0004057919,0.0004786644,0.0006481329,0.000777835,0.0007046598,0.003525172],"category_scores_gemma":[0.002761373,0.000234706,0.0003050463,0.0003504471,0.0006299266,0.000328908,0.0006894831,0.0006486028,0.000935684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008236576,"about_ca_system_score_gemma":0.001419095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01385993,"about_ca_topic_score_gemma":0.01262866,"domain_scores_codex":[0.998952,0.0004806996,0.00004241891,0.0001271584,0.0002927471,0.0001049612],"domain_scores_gemma":[0.9979522,0.0006255193,0.0001657323,0.0001905705,0.0003609646,0.0007051018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0522943,0.0136767,0.7492351,0.0003304019,0.0005179786,0.004164741,0.001902085,0.0003732538,0.06780758,0.0003812553,0.01237227,0.09694432],"study_design_scores_gemma":[0.002860012,0.02726633,0.9469078,0.00004021499,0.0002330672,0.00316785,0.0005768547,0.0004831543,0.009362146,0.0001283398,0.008934284,0.00004003873],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929133,0.0005224075,0.0005028009,0.0008288116,0.00002143765,0.0004513861,0.001055098,0.00003041725,0.003674348],"genre_scores_gemma":[0.9889649,0.000457968,0.002065411,0.0007636303,0.00009688306,0.0002686808,0.003081107,0.00004985867,0.004251473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01385993,"threshold_uncertainty_score":0.02755851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1383665251954815,"score_gpt":0.5183740489704546,"score_spread":0.3800075237749731,"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."}}