{"id":"W4313379144","doi":"10.1364/boe.473447","title":"Adaptive optics scanning laser ophthalmoscopy and optical coherence tomography (AO-SLO-OCT) system for in vivo mouse retina imaging","year":2022,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Eye Institute; Dalian University of Technology; National Natural Science Foundation of China; Canadian Institutes of Health Research; Oregon Health and Science University; National Science Foundation","keywords":"Optical coherence tomography; Scanning laser ophthalmoscopy; Adaptive optics; Retina; Optics; Preclinical imaging; Ophthalmoscopy; In vivo; Tomography; Laser; Coherence (philosophical gambling strategy); Ophthalmology; Medicine; Physics; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005507434,0.0003903592,0.0004823405,0.000444584,0.0002955708,0.0001224098,0.000596732,0.0001573568,0.00005526494],"category_scores_gemma":[0.00008405873,0.0004308049,0.0001358034,0.001072163,0.0005014624,0.0001830755,0.0003506776,0.0006450478,0.000003825927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001926068,"about_ca_system_score_gemma":0.00005839807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001928487,"about_ca_topic_score_gemma":0.00000168946,"domain_scores_codex":[0.9971374,0.00007394132,0.0006744114,0.0006363732,0.0006568711,0.0008210081],"domain_scores_gemma":[0.998264,0.0005421371,0.00008784315,0.0005040236,0.0001048992,0.0004971212],"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":[0.001424979,0.003882132,0.01618053,0.005846674,0.001157145,0.00105674,0.00567817,0.07268803,0.6877066,0.1805863,0.01330123,0.01049149],"study_design_scores_gemma":[0.004719387,0.001088678,0.0008833396,0.0006818212,0.0002669306,0.0002599919,0.009594746,0.9135994,0.06024553,0.001260605,0.004870442,0.002529086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.87027,0.001034223,0.1111954,0.000472508,0.001098407,0.003534503,0.001418338,0.001427423,0.009549211],"genre_scores_gemma":[0.9249417,0.00001938493,0.07310146,0.00003330563,0.000119682,0.001607637,0.0000424389,0.00008887648,0.00004554666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8409114,"threshold_uncertainty_score":0.9998144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01255798699030898,"score_gpt":0.2415221213020812,"score_spread":0.2289641343117723,"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."}}