{"id":"W2895925819","doi":"10.1364/ol.43.005162","title":"Visible light sensorless adaptive optics for retinal structure and fluorescence imaging","year":2018,"lang":"en","type":"article","venue":"Optics Letters","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Alzheimer Society Research Program; National Research Foundation of Korea; Michael Smith Health Research BC","keywords":"Optical coherence tomography; Optics; Supercontinuum; Adaptive optics; Fluorescence-lifetime imaging microscopy; Materials science; Coherence (philosophical gambling strategy); Retinal; Visible spectrum; Fluorescence; Physics; Wavelength; Photonic-crystal fiber; Medicine","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":[0.000107507,0.0002478233,0.0001556876,0.0001523529,0.0001335664,0.0003181964,0.000305521,0.000264899,0.0008987679],"category_scores_gemma":[0.0002375934,0.000135395,0.0001179309,0.0002009308,0.0002327665,0.000384601,0.0002639523,0.0003290329,0.0003946529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000369306,"about_ca_system_score_gemma":0.0003146008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004925324,"about_ca_topic_score_gemma":0.001118482,"domain_scores_codex":[0.9998726,0.00001202763,0.00000597552,0.00002827169,0.00007065148,0.00001051607],"domain_scores_gemma":[0.9999098,0.00002146327,0.00002590457,0.00001133731,0.00002268414,0.000008953046],"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":[0.00005778082,0.00001565181,0.0001909982,0.00004535519,0.000003162818,0.00003778187,0.00002397355,0.00068036,0.9655597,0.003797225,0.0005290683,0.02905902],"study_design_scores_gemma":[0.00001778237,0.0002271301,0.001127905,0.00001578342,0.00001666679,0.0003182702,0.00001655419,0.04865612,0.9228142,0.001749955,0.02500173,0.00003787185],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3330236,0.007482641,0.6343932,0.00144017,0.0003848329,0.0001616399,0.0003760775,0.002270767,0.02046709],"genre_scores_gemma":[0.729336,0.002263358,0.2590556,0.0002875066,0.0001156544,0.00008933761,0.0001587343,0.0001212387,0.008572481],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008987679,"threshold_uncertainty_score":0.003006697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007794760698298058,"score_gpt":0.2203235674842534,"score_spread":0.2125288067859553,"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."}}