{"id":"W109227896","doi":"10.1007/978-3-540-36841-0_348","title":"Automated Calcification Detection and Quantification in Intravascular Ultrasound Images by Adaptive Thresholding","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Aging","funders":"","keywords":"Thresholding; Receiver operating characteristic; Intravascular ultrasound; Artificial intelligence; Ultrasound; Pattern recognition (psychology); Discriminant; Computer science; Acoustic shadow; Computer vision; Mathematics; Image (mathematics); Radiology; Medicine; Statistics","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":[0.0005116847,0.0008590536,0.0008580933,0.00108989,0.0001671123,0.001407606,0.001319367,0.0009356946,0.007224756],"category_scores_gemma":[0.001047878,0.0007408567,0.0004912051,0.001061931,0.0005142502,0.0009846293,0.0004500647,0.0009864795,0.007005872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002423976,"about_ca_system_score_gemma":0.0003218385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004888347,"about_ca_topic_score_gemma":0.001110558,"domain_scores_codex":[0.9996852,0.00002810672,0.00001776456,0.00007110956,0.0001849578,0.00001296704],"domain_scores_gemma":[0.9994623,0.0003003296,0.00002478178,0.0000637148,0.000138018,0.00001091753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000372483,0.00002566455,0.0002347656,0.0004082645,0.00002751102,0.000095029,0.00005321308,0.004528954,0.0842208,0.01053932,0.01526343,0.8845658],"study_design_scores_gemma":[0.00003461698,0.0001859384,0.005680192,0.0004626105,0.0002024701,0.007465736,0.00009813789,0.2385335,0.3268236,0.06285851,0.3574491,0.0002055608],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002505862,0.0101689,0.9731528,0.0002126982,0.0003455021,0.00005156445,0.000181814,0.001858848,0.01152206],"genre_scores_gemma":[0.02167836,0.01086148,0.9189065,0.0001948641,0.0002137976,0.0000736164,0.0004355548,0.0007701175,0.04686576],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007224756,"threshold_uncertainty_score":0.02416927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02131394262220684,"score_gpt":0.2692765101383754,"score_spread":0.2479625675161686,"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."}}