{"id":"W4315874448","doi":"10.1364/boe.484257","title":"Localized transverse flow measurement with dynamic light scattering line-scan OCT","year":2023,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; National Medical Research Council; National Research Foundation Singapore; Medical Research Council Canada; Canadian Institutes of Health Research; University of Waterloo; National Research Foundation","keywords":"Optics; Optical coherence tomography; Transverse plane; Line (geometry); Light scattering; Flow (mathematics); Scattering; Materials science; Physics; Medicine; Radiology","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":[0.0002536677,0.0002665742,0.0002708219,0.0002470068,0.00008860212,0.00006035085,0.0003832846,0.0001562729,0.00009622599],"category_scores_gemma":[0.00002380618,0.0002301422,0.00009604266,0.001148284,0.0002186657,0.00008822272,0.00004633995,0.0002684439,0.0002080583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001053321,"about_ca_system_score_gemma":0.00004103391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005012878,"about_ca_topic_score_gemma":0.00001388853,"domain_scores_codex":[0.9979017,0.00002105444,0.0003463915,0.0003310851,0.0008448164,0.0005549377],"domain_scores_gemma":[0.998947,0.00005242251,0.00002583899,0.0004725468,0.00008875937,0.0004134614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001682639,0.0006870535,0.0001087139,0.001306957,0.0008923214,0.0002592887,0.001479988,0.0906013,0.8353944,0.001410777,0.01129782,0.05639306],"study_design_scores_gemma":[0.001592509,0.0002082905,0.0003226124,0.0003272211,0.0001271145,0.00001144026,0.0001812948,0.9319925,0.01059894,0.0001848994,0.05370032,0.0007528389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1221007,0.0004912583,0.8600721,0.0032027,0.0009556417,0.0015569,0.0002147807,0.005261626,0.006144292],"genre_scores_gemma":[0.9767774,0.0001423754,0.02243943,0.00003582822,0.0001056425,0.0002940471,0.00006969576,0.00008580579,0.00004982559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8546766,"threshold_uncertainty_score":0.9384927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715152884746113,"score_gpt":0.2312269468137072,"score_spread":0.214075417966246,"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."}}