{"id":"W4411291454","doi":"10.1158/1557-3265.sabcs24-p1-01-05","title":"Abstract P1-01-05: Conducting Ancillary Studies during an Active NCTN/NCORP Screening Trial – The TMIST (ECOG-ACRIN EA1151) Experience","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Oncology; Internal medicine","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":[0.0577864,0.0005180597,0.0009561399,0.0002582491,0.00201472,0.001853346,0.001243528,0.002212424,0.01955455],"category_scores_gemma":[0.05269109,0.0004605539,0.0008429689,0.000432516,0.0008297078,0.001511389,0.001632718,0.003716287,0.003885831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001524094,"about_ca_system_score_gemma":0.01086477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002680924,"about_ca_topic_score_gemma":0.004918693,"domain_scores_codex":[0.9753508,0.02122264,0.0005993517,0.0007892008,0.001086849,0.0009510332],"domain_scores_gemma":[0.958591,0.01693311,0.004158653,0.004707003,0.003887591,0.01172263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.3161061,0.03509761,0.0405424,0.00204593,0.000959662,0.001000341,0.003775233,0.0008731166,0.003062094,0.00306396,0.2212177,0.3722558],"study_design_scores_gemma":[0.365561,0.3099558,0.1220103,0.002651492,0.001088975,0.001128825,0.002665567,0.003344702,0.00407567,0.004863024,0.1824258,0.0002288364],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7615275,0.003310611,0.008935643,0.04144254,0.004452889,0.08489364,0.008703819,0.00104187,0.08569141],"genre_scores_gemma":[0.7852722,0.001702925,0.02853634,0.0256833,0.004386358,0.1292062,0.005702275,0.0002785938,0.01923181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0577864,"threshold_uncertainty_score":0.3056073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5735997401750292,"score_gpt":0.6294568798058396,"score_spread":0.0558571396308104,"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."}}