{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004345022,0.0002248695,0.0003655866,0.000246109,0.00002599777,0.00001666473,0.0004195978,0.000250443,0.0004406499],"category_scores_gemma":[0.0001021109,0.0002139369,0.0001768568,0.001016534,0.0005637967,0.0002382202,0.0000930517,0.0003256931,0.00002827913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004420349,"about_ca_system_score_gemma":0.00002068731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001340227,"about_ca_topic_score_gemma":0.000002547416,"domain_scores_codex":[0.9979829,0.00004098286,0.0005595728,0.0002506927,0.0005347261,0.0006311524],"domain_scores_gemma":[0.9985632,0.0002382421,0.00003989566,0.0006105881,0.00006466386,0.0004834513],"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":[0.00009221239,0.00545208,0.09384321,0.001256497,0.0004265302,0.00003226325,0.001449599,0.0008825239,0.7813492,0.102804,0.008207909,0.004203951],"study_design_scores_gemma":[0.00970223,0.0009544375,0.1753496,0.0008518809,0.000602183,0.0001452323,0.001067211,0.04168015,0.682682,0.01544519,0.0662686,0.005251315],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9488718,0.001140064,0.0349744,0.0001351817,0.0006140184,0.0009124699,0.0001215586,0.000322642,0.01290789],"genre_scores_gemma":[0.97092,0.00004454964,0.02869841,0.00002390299,0.0001233796,0.0001421767,0.00000858266,0.00002755203,0.00001142678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09866726,"threshold_uncertainty_score":0.8724095,"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."}}