{"id":"W4386212716","doi":"10.1007/s00266-023-03566-x","title":"Invited Discussion on: Assessment of Three Breast Volume Measurement Techniques—Single Marking, MRI and Crisalix 3D Software","year":2023,"lang":"en","type":"letter","venue":"Aesthetic Plastic Surgery","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Otorhinolaryngology; Volume (thermodynamics); Plastic surgery; Medical physics; Software; Nuclear medicine; Radiology; Biomedical engineering; Surgery; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001396464,0.0007354399,0.001565516,0.0009555302,0.0001014924,0.0000545682,0.0002203683,0.0008592563,0.0002006099],"category_scores_gemma":[0.0006081235,0.0005364013,0.0003651116,0.0005321943,0.0003206463,0.00006008563,0.0001898502,0.001469921,0.00003034818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000816325,"about_ca_system_score_gemma":0.0004289084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001355241,"about_ca_topic_score_gemma":0.00003665917,"domain_scores_codex":[0.9945934,0.0002694426,0.001050242,0.001021764,0.002326954,0.0007382047],"domain_scores_gemma":[0.9956357,0.002051945,0.0006637347,0.001055506,0.0003753465,0.0002177133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006105263,0.0002562651,0.06245944,0.001218944,0.000125432,0.0009008076,0.00002154431,0.000004485446,0.0000381413,7.239068e-7,0.9005159,0.03439725],"study_design_scores_gemma":[0.0007929449,0.000921547,0.0951537,0.02282632,0.001352221,0.001374942,0.00002358092,0.0003265885,0.0001887337,0.000134425,0.8756595,0.001245489],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.003532093,0.0003336361,0.005711103,0.9836649,0.003934323,0.001445165,0.0004060654,0.0007929985,0.0001797332],"genre_scores_gemma":[0.08165766,0.003428206,0.01973795,0.8722119,0.009963443,0.004404159,0.003962367,0.00283172,0.001802617],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.111453,"threshold_uncertainty_score":0.9997088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05226400781048762,"score_gpt":0.2766203826399315,"score_spread":0.2243563748294439,"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."}}