{"id":"W2234466563","doi":"10.1007/978-3-319-13909-8_10","title":"Confidence Weighted Local Phase Features for Robust Bone Surface Segmentation in Ultrasound","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Pelvic and Acetabular Injuries","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ground truth; Artificial intelligence; Computer vision; Segmentation; Computer science; Imaging phantom; Visualization; Image segmentation; Image quality; Image (mathematics); Radiology; Medicine","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":[0.0008766234,0.0007003189,0.001039021,0.001217363,0.0002355157,0.001248158,0.001563842,0.001324829,0.003389176],"category_scores_gemma":[0.003601224,0.0007082877,0.0007357544,0.001538927,0.0004510584,0.001260295,0.001322422,0.00137836,0.001450627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003924108,"about_ca_system_score_gemma":0.0005076061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001689177,"about_ca_topic_score_gemma":0.002194758,"domain_scores_codex":[0.999508,0.00007795332,0.00003307375,0.00008174793,0.0002538791,0.00004528205],"domain_scores_gemma":[0.9988287,0.000646283,0.0001215559,0.0001256067,0.0002479075,0.00002995968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002272948,0.00005900863,0.0003720888,0.0002420971,0.0000437595,0.00007606825,0.00005900547,0.08053288,0.04922837,0.007180117,0.00534366,0.8566356],"study_design_scores_gemma":[0.00001025866,0.00005827563,0.0006929611,0.00002601993,0.00002553087,0.0001640087,0.00001638554,0.9722852,0.01900751,0.004970911,0.002723461,0.00001951801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005104683,0.0005886298,0.9928248,0.00008197152,0.00003711372,0.00002170476,0.00009179499,0.000742836,0.0005063603],"genre_scores_gemma":[0.1902452,0.001310518,0.8024968,0.0001200568,0.000151593,0.0001034118,0.0007409808,0.0008002337,0.004031218],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003389176,"threshold_uncertainty_score":0.01133794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01684303318932079,"score_gpt":0.286022178079671,"score_spread":0.2691791448903502,"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."}}