{"id":"W4403457267","doi":"10.1101/2024.10.15.24315514","title":"In-Patient Repeatability and Sensitivity Study of Multi-Plane Super-Resolution Ultrasound in Breast Cancer","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research","funders":"China Scholarship Council; Imperial College London; National Institute for Health and Care Research; Cancer Research UK; Royal Marsden NHS Foundation Trust","keywords":"Repeatability; Sensitivity (control systems); Breast cancer; Ultrasound; Resolution (logic); Medicine; Materials science; Optics; Cancer; Medical physics; Biomedical engineering; Radiology; Computer science; Physics; Internal medicine; Mathematics; Artificial intelligence; Statistics; Electronic engineering; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005350359,0.00035478,0.000504905,0.0006076643,0.0002249067,0.000493865,0.0003625666,0.0005174786,0.0006174486],"category_scores_gemma":[0.01549223,0.0003468762,0.0003129247,0.0004414178,0.0002902234,0.0003550092,0.0004807922,0.0002631249,0.0002298987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002063052,"about_ca_system_score_gemma":0.0001824273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004831957,"about_ca_topic_score_gemma":0.000609895,"domain_scores_codex":[0.9957137,0.002247552,0.000224269,0.0008544967,0.0008075612,0.0001524813],"domain_scores_gemma":[0.9849815,0.00805197,0.002737005,0.001994253,0.001977388,0.0002579058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005251868,0.0004136555,0.681188,0.0005765673,0.0009719724,0.0004588164,0.001884015,0.00615091,0.2139892,0.0002465839,0.0005715424,0.08829688],"study_design_scores_gemma":[0.00004107445,0.002916463,0.9201213,0.00002100268,0.0004895984,0.001731031,0.0003954917,0.01443093,0.0579475,0.0001823197,0.001664225,0.00005902922],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840658,0.000894597,0.01402661,0.00002959359,0.00001995502,0.00005401499,0.0001745738,0.0001163618,0.000618438],"genre_scores_gemma":[0.9968177,0.00005424086,0.002871745,0.00001585861,0.00001351688,0.0000238015,0.00007853968,0.00002377782,0.0001007972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005350359,"threshold_uncertainty_score":0.02829576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02812401226731657,"score_gpt":0.3208426928091971,"score_spread":0.2927186805418805,"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."}}