{"id":"W4413371775","doi":"10.3390/cancers17162706","title":"A Priori Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy Using CT Radiomics","year":2025,"lang":"en","type":"article","venue":"Cancers","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Terry Fox Research Institute; University of Toronto; Terry Fox Foundation","keywords":"Medicine; Radiomics; Breast cancer; Complete response; Neoadjuvant therapy; Radiology; Cancer; Chemotherapy; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003568507,0.0001156847,0.0002948703,0.0002082926,0.00005513504,0.00001018698,0.0000881048,0.00003744569,0.00006867247],"category_scores_gemma":[0.0001329143,0.0001056211,0.00007918659,0.0004272732,0.00008844088,0.00003734239,0.00002171191,0.0002102284,9.609698e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001639576,"about_ca_system_score_gemma":0.001509185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001771273,"about_ca_topic_score_gemma":0.00000638592,"domain_scores_codex":[0.9990912,0.00004226351,0.000254993,0.0002265012,0.000177774,0.0002072417],"domain_scores_gemma":[0.9994223,0.00004165746,0.00007742301,0.0002285933,0.00008890141,0.0001411032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.007356802,0.00004978798,0.05617454,0.0003288239,0.0003997211,0.00004925653,0.001271448,0.02020017,0.5938072,0.00008307993,0.009456881,0.3108223],"study_design_scores_gemma":[0.01026255,0.0003486515,0.4714449,0.003713634,0.0004630784,0.0003239502,0.0005038425,0.3775223,0.01770432,0.00007054993,0.117265,0.0003771264],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854347,0.0005444596,0.005082023,0.007479541,0.000744196,0.0003276825,0.00004294768,0.00004625562,0.0002982612],"genre_scores_gemma":[0.9917557,0.0003282447,0.003061215,0.00375682,0.0002291335,0.00002015481,0.000004240423,0.00002709899,0.0008174313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5761029,"threshold_uncertainty_score":0.4307104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111965939185374,"score_gpt":0.3178448500522599,"score_spread":0.3067251906604062,"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."}}