{"id":"W4391565960","doi":"10.1097/gox.0000000000005599","title":"Machine Learning to Predict the Need for Postmastectomy Radiotherapy after Immediate Breast Reconstruction","year":2024,"lang":"en","type":"article","venue":"Plastic & Reconstructive Surgery Global Open","topic":"Breast Implant and Reconstruction","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Logistic regression; Medicine; Receiver operating characteristic; Confidence interval; Lasso (programming language); Machine learning; Cohort; Brier score; Retrospective cohort study; Breast cancer; Artificial intelligence; Internal medicine; Computer science; Cancer","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":[0.002899235,0.0005019861,0.0005363776,0.001055568,0.0001649737,0.0006964291,0.0004758835,0.0004714044,0.0008421736],"category_scores_gemma":[0.00851672,0.0001567136,0.0007125645,0.0006134263,0.0001930415,0.0004197575,0.0003634295,0.0008737847,0.0002625981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003856086,"about_ca_system_score_gemma":0.0006309722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002022516,"about_ca_topic_score_gemma":0.001797571,"domain_scores_codex":[0.9993024,0.0003035732,0.00007095229,0.000139143,0.000113533,0.00007030125],"domain_scores_gemma":[0.995385,0.003200125,0.0007662718,0.0001415333,0.0003951282,0.0001119639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007047075,0.000515831,0.7257249,0.0001625293,0.0004297906,0.0002099439,0.00007120029,0.1540679,0.0007452158,0.0003148949,0.002926675,0.1141266],"study_design_scores_gemma":[0.0000545669,0.0005567554,0.08329284,0.0001038366,0.0001884668,0.0004375805,0.00008119602,0.9119667,0.0009344149,0.001346831,0.001010887,0.00002594661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.952377,0.002220619,0.04120379,0.001121108,0.00009426449,0.00008034837,0.001340742,0.0002401575,0.001322113],"genre_scores_gemma":[0.9907445,0.00030949,0.007313607,0.00008054203,0.00005238431,0.00004010068,0.001189705,0.000008746686,0.0002608495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002899235,"threshold_uncertainty_score":0.01533276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01285775689767684,"score_gpt":0.2599329087099059,"score_spread":0.247075151812229,"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."}}