{"id":"W2061627518","doi":"10.1364/boe.1.001309","title":"High-speed spectral domain optical coherence tomography using non-uniform fast Fourier transform","year":2010,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Optical coherence tomography; Optics; Fourier transform; Image processing; Hyperspectral imaging; Signal processing; Optical tomography; Computer science; Fourier domain; Tomography; Artificial intelligence; Computer vision; Physics; Digital signal processing; Image (mathematics)","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":[0.0005028927,0.0002712508,0.0002683052,0.0003327178,0.000186977,0.0003481881,0.000258269,0.0003521486,0.001008042],"category_scores_gemma":[0.00105592,0.0001733245,0.0001273096,0.0005124696,0.0003933833,0.0008141847,0.0003465854,0.0003052622,0.000215814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002812586,"about_ca_system_score_gemma":0.0004485481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001252203,"about_ca_topic_score_gemma":0.004365438,"domain_scores_codex":[0.9997599,0.00004602011,0.00001398696,0.00003861208,0.0001243602,0.00001728068],"domain_scores_gemma":[0.9995306,0.0002422154,0.00005588813,0.0000535875,0.0001014119,0.0000163866],"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":[0.0003087994,0.00007164024,0.001528225,0.0001927639,0.00002087384,0.0002114778,0.00007358918,0.003344422,0.8700755,0.002535217,0.0009507318,0.1206867],"study_design_scores_gemma":[0.0001382597,0.0005305729,0.01056502,0.00005434636,0.00003635908,0.001746909,0.00006972982,0.1861866,0.7885993,0.002723889,0.00927149,0.00007742938],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4519967,0.002119988,0.5381161,0.0005056016,0.0000940115,0.000154085,0.0002862578,0.001045165,0.005682077],"genre_scores_gemma":[0.5785437,0.001013808,0.4182222,0.000100924,0.00002995556,0.000103052,0.0002307681,0.0000430138,0.001712692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001252203,"threshold_uncertainty_score":0.003372192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009414505106127102,"score_gpt":0.2333418155629116,"score_spread":0.2239273104567845,"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."}}