{"id":"W4403018285","doi":"10.52054/fvvo.16.3.042","title":"Achieving successful outcomes with endometrial ablation needs better case selection","year":2024,"lang":"en","type":"article","venue":"Facts Views and Vision in ObGyn","topic":"Uterine Myomas and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Endometrial ablation; Selection (genetic algorithm); Ablation; Case selection; Computer science; Medicine; Internal medicine; Surgery; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01988339,0.00109574,0.002469792,0.003817329,0.002042946,0.008275284,0.002223664,0.002413649,0.02195643],"category_scores_gemma":[0.06347579,0.0005822994,0.002063478,0.001402049,0.001882473,0.0116316,0.003975818,0.00665635,0.008934901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002601446,"about_ca_system_score_gemma":0.004948326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002565884,"about_ca_topic_score_gemma":0.003749131,"domain_scores_codex":[0.9865107,0.005344127,0.002452255,0.001427863,0.003537248,0.0007279683],"domain_scores_gemma":[0.9548535,0.02333182,0.00434398,0.004588551,0.008732112,0.004149891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006795715,0.0004347035,0.04907399,0.001424748,0.0002168239,0.00503715,0.001618986,0.001850588,0.001125084,0.01077744,0.1726028,0.755158],"study_design_scores_gemma":[0.0007446252,0.001026806,0.1160713,0.02424176,0.0004145572,0.05122093,0.0130188,0.005988015,0.001994259,0.2078298,0.5765373,0.0009117185],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0865842,0.1545365,0.1408594,0.4692531,0.03089256,0.004552301,0.002438089,0.001744169,0.1091396],"genre_scores_gemma":[0.5199667,0.1026647,0.1898049,0.092637,0.06988793,0.005622954,0.005170558,0.002117784,0.01212755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02195643,"threshold_uncertainty_score":0.1051547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02482595811910249,"score_gpt":0.3462885933485705,"score_spread":0.321462635229468,"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."}}