{"id":"W2994015183","doi":"","title":"Imaging the mouse retina in vivo using Adaptive Optics - Fourier Domain Optical Coherence Tomography","year":2013,"lang":"en","type":"article","venue":"Investigative Ophthalmology & Visual Science","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Optical coherence tomography; Fourier domain; Adaptive optics; Optics; Retina; Fourier transform; Coherence (philosophical gambling strategy); Physics; Optical tomography; Preclinical imaging; In vivo; Tomography; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0007894957,0.0003555235,0.0003043608,0.000375454,0.0004228822,0.000190122,0.001037158,0.000123852,0.0002039014],"category_scores_gemma":[0.0002471088,0.0002892794,0.00008582249,0.003388394,0.009201164,0.0008230768,0.0002565706,0.0006668599,0.00006673842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001710146,"about_ca_system_score_gemma":0.0001586897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001602556,"about_ca_topic_score_gemma":0.000006116352,"domain_scores_codex":[0.9972156,0.0001451067,0.0004691481,0.0006545607,0.0005256007,0.0009900397],"domain_scores_gemma":[0.9983546,0.0003844182,0.00009331998,0.000502185,0.0002673893,0.0003981032],"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":[0.000005986826,0.00008776105,0.03363428,0.00001081247,0.00002017256,0.00004844449,0.0008944377,0.003599884,0.9540399,0.007352083,0.0000521616,0.0002540288],"study_design_scores_gemma":[0.0005237074,0.0003447656,0.1146332,0.0001244733,0.00004147181,0.0003590612,0.003314873,0.3918523,0.3849261,0.1025892,0.0000288155,0.001262013],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902198,0.00007160547,0.0004467549,0.0002733965,0.000110458,0.0008633851,0.000009459496,0.0001431489,0.007861957],"genre_scores_gemma":[0.9551119,0.000002190611,0.04437719,0.0001076726,0.00004279587,0.0003076534,0.000001137871,0.00003119115,0.00001833211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5691139,"threshold_uncertainty_score":0.999956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02975041906642334,"score_gpt":0.2930808173851199,"score_spread":0.2633303983186965,"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."}}