{"id":"W2111432139","doi":"10.1002/lsm.20449","title":"Ex vivo imaging of chronic total occlusions using forward‐looking optical coherence tomography","year":2006,"lang":"en","type":"article","venue":"Lasers in Surgery and Medicine","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; St. Michael's Hospital; Sunnybrook Health Science Centre; Ontario Institute for Cancer Research; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Optical coherence tomography; Ex vivo; Radiology; Lumen (anatomy); Percutaneous; Angioplasty; Angiography; Occlusion; Conventional PCI; Peripheral; Critical limb ischemia; Biomedical engineering; In vivo; Vascular disease; Surgery; Arterial disease; Myocardial infarction; Cardiology; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003600935,0.0002217014,0.0001187277,0.0003541278,0.0001652732,0.0003319773,0.00009712188,0.0003197726,0.0009068284],"category_scores_gemma":[0.0003721307,0.0001904965,0.00009001399,0.0001344739,0.0002512596,0.0002731877,0.0001369674,0.000301874,0.0001329722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001548026,"about_ca_system_score_gemma":0.0001534514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005750856,"about_ca_topic_score_gemma":0.0008344508,"domain_scores_codex":[0.9999027,0.00002582196,0.000008261311,0.00001734001,0.0000248225,0.00002103158],"domain_scores_gemma":[0.9997515,0.00007871633,0.00006718122,0.00002396078,0.00005061553,0.00002796169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006175906,0.0001349572,0.005774819,0.00008887696,0.00001449358,0.0002444188,0.00007583296,0.0002914341,0.9857036,0.0001196055,0.0001401873,0.006794184],"study_design_scores_gemma":[0.0002164171,0.003209224,0.1945934,0.00006653424,0.0001342899,0.008654045,0.0002743628,0.01422389,0.773117,0.0003754436,0.005088423,0.00004699976],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835563,0.001011677,0.01409536,0.00008295906,0.000009259497,0.00003514477,0.0001946916,0.00004423732,0.0009703135],"genre_scores_gemma":[0.9855407,0.0007126599,0.01264304,0.00008691385,0.00001748396,0.00005352274,0.0002590916,0.000009701052,0.0006768016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009068284,"threshold_uncertainty_score":0.003033638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00898549194398106,"score_gpt":0.2367247936462446,"score_spread":0.2277393017022636,"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."}}