{"id":"W1994179532","doi":"10.1364/boe.3.002600","title":"In vivo feasibility of endovascular Doppler optical coherence tomography","year":2012,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; Colibri Technologies (Canada); Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Deutscher Akademischer Austauschdienst","keywords":"Optical coherence tomography; Optics; Doppler effect; Preclinical imaging; Tomography; Coherence (philosophical gambling strategy); In vivo; Medical physics; Biomedical engineering; Medicine; Physics; Biology","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":[0.0008893277,0.0003056294,0.0002069145,0.0002210607,0.0001503618,0.0004860422,0.0002304909,0.0004991376,0.000738341],"category_scores_gemma":[0.001489327,0.0003157062,0.0001407979,0.0000611336,0.0004674405,0.0004968622,0.000232114,0.0004586468,0.0002060636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001329303,"about_ca_system_score_gemma":0.0002529566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000291658,"about_ca_topic_score_gemma":0.0002456159,"domain_scores_codex":[0.9997279,0.0001244839,0.0000122996,0.00004811021,0.00004896627,0.00003828353],"domain_scores_gemma":[0.9990682,0.0005564157,0.0001215427,0.0001204598,0.00007847999,0.00005486609],"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":[0.0005172397,0.00007289978,0.0005737935,0.00004576563,0.000007735614,0.000184828,0.00003669574,0.0002990479,0.993134,0.0002252004,0.00007385576,0.004828944],"study_design_scores_gemma":[0.00007491787,0.004823987,0.007093538,0.00002323354,0.00007618769,0.002111735,0.00005794379,0.01209749,0.970229,0.0002500472,0.003132735,0.00002910314],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9200001,0.001456687,0.07618213,0.0002625579,0.00008064167,0.00006460975,0.00008924994,0.0002213941,0.001642727],"genre_scores_gemma":[0.9687603,0.000905871,0.02859585,0.0001015404,0.00005551721,0.0001072751,0.000142735,0.00004193393,0.001288957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008893277,"threshold_uncertainty_score":0.004703283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02134081348584783,"score_gpt":0.2641675022059599,"score_spread":0.242826688720112,"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."}}