{"id":"W2606954399","doi":"10.1038/srep45733","title":"A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound","year":2017,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Canadian Institutes of Health Research; Terry Fox Foundation","keywords":"Breast cancer; Medicine; Chemotherapy; Neoadjuvant therapy; Oncology; Ultrasound; Breast ultrasound; Radiology; Internal medicine; Cancer; Mammography","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":[0.002080377,0.00009576968,0.0002551171,0.0001543462,0.0002449821,0.0001079629,0.00006096531,0.00004690489,0.00002590774],"category_scores_gemma":[0.001063581,0.00007956327,0.00004034057,0.0001129163,0.000505013,0.0001674217,0.00003431867,0.0001605432,2.716943e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007571487,"about_ca_system_score_gemma":0.0002054509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009184203,"about_ca_topic_score_gemma":0.00001922309,"domain_scores_codex":[0.9985783,0.00006605164,0.0003801705,0.0003925465,0.0004045856,0.000178396],"domain_scores_gemma":[0.9987662,0.00005842033,0.0004395753,0.0004472447,0.0001846617,0.0001039294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003691814,0.0001069736,0.892774,0.00003654495,0.00001896563,0.0000727005,0.0008756305,0.00002508897,0.1014195,0.000005117368,0.0001425552,0.004153737],"study_design_scores_gemma":[0.0009821167,0.000056636,0.9914768,0.000336402,0.00002413906,0.0001748858,0.00009013899,0.005186719,0.00101872,0.0001457759,0.0004436439,0.00006401724],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964216,0.00008191496,0.00008194367,0.0005967957,0.00245055,0.0002451511,0.00001174237,0.00001161261,0.00009868357],"genre_scores_gemma":[0.9989125,0.00002716385,0.0007681934,0.00002357817,0.0000383462,0.00000373102,0.000009988272,0.00001327495,0.000203202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1004007,"threshold_uncertainty_score":0.3244496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02045556662078633,"score_gpt":0.3320946141403754,"score_spread":0.311639047519589,"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."}}