{"id":"W3182147653","doi":"10.1364/ol.430915","title":"Phase-corrected buffer averaging for enhanced OCT angiography using FDML laser","year":2021,"lang":"en","type":"article","venue":"Optics Letters","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Optics; Optical coherence tomography; Frame rate; Ultrashort pulse; Laser; Coherence (philosophical gambling strategy); Mode-locking; Materials science; Computer science; Physics","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":[0.00006090798,0.0001939993,0.0001879477,0.0001595415,0.0001068916,0.00009340787,0.0001364268,0.00007372569,0.00005363682],"category_scores_gemma":[0.0000261449,0.0002297214,0.0002771906,0.0007940984,0.00005195389,0.0001240184,0.00002314229,0.0001638486,0.00001352605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000412951,"about_ca_system_score_gemma":0.00001441344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002552309,"about_ca_topic_score_gemma":0.000002950692,"domain_scores_codex":[0.9989552,0.00001481122,0.0002237628,0.0002681937,0.0001360631,0.0004019328],"domain_scores_gemma":[0.9992881,0.0001354803,0.00002865192,0.0003429752,0.00009987848,0.0001048863],"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":[0.000007944611,0.0001014319,0.00008941359,0.00005796519,0.000189251,0.000008388462,0.0001551131,0.02726221,0.9686377,0.0003036071,0.001291089,0.001895851],"study_design_scores_gemma":[0.002415064,0.0000597269,0.0002544387,0.0001023641,0.0003223903,0.00001370413,0.0001398816,0.3425898,0.6485875,0.000362509,0.004214094,0.000938511],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5653477,0.00009192988,0.4326319,0.0002428711,0.0002731727,0.0002360534,0.00003604683,0.0002720136,0.0008683421],"genre_scores_gemma":[0.889205,0.00001367119,0.1097792,0.0005886062,0.0001415064,0.0001100341,0.00007719143,0.00006422483,0.00002052906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3238573,"threshold_uncertainty_score":0.9367766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01627746854119656,"score_gpt":0.257931514206531,"score_spread":0.2416540456653345,"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."}}