{"id":"W2510102196","doi":"10.1038/srep32223","title":"Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Eye Institute; Canadian Institutes of Health Research; University of California, Davis; Fondation pour la Recherche sur Alzheimer; Genome British Columbia; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Michael Smith Health Research BC; National Science Foundation","keywords":"Optics; Adaptive optics; Wavefront; Optical coherence tomography; Coherence (philosophical gambling strategy); Deformable mirror; Physics; Interferometry; Femtosecond; Two-photon excitation microscopy; Laser; Materials science; Fluorescence","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":[0.0001769807,0.0002771275,0.0001812438,0.0002137593,0.000129884,0.0003129459,0.0005853943,0.000256772,0.0004735337],"category_scores_gemma":[0.0003061433,0.0001927612,0.0001461106,0.0002164501,0.0003729453,0.0004522993,0.0004065609,0.0003497897,0.0001189275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005041572,"about_ca_system_score_gemma":0.000408525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009389647,"about_ca_topic_score_gemma":0.002583468,"domain_scores_codex":[0.9997532,0.00001948443,0.0000157435,0.00006097709,0.0001267871,0.00002379595],"domain_scores_gemma":[0.9997535,0.00004975459,0.00009278173,0.00002734039,0.00004611639,0.00003042337],"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":[0.00002696086,0.00001056707,0.0001855234,0.00001540758,0.000002641704,0.00001581671,0.00001107806,0.0001503974,0.9968879,0.0002454004,0.00003355154,0.002414778],"study_design_scores_gemma":[0.000009696154,0.0001083415,0.001335365,0.000002117781,0.00000547581,0.0001252805,0.000007570958,0.01041818,0.9871422,0.000106432,0.0007264876,0.0000127769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8774517,0.000470483,0.1193698,0.0001572102,0.00003304031,0.00007540459,0.0001662159,0.0003709927,0.001905138],"genre_scores_gemma":[0.9318839,0.0002213816,0.06623991,0.00007083085,0.00001119966,0.00003944196,0.00009075437,0.00002935447,0.001413124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009389647,"threshold_uncertainty_score":0.003657877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009956115692495552,"score_gpt":0.2672657863960179,"score_spread":0.2573096707035224,"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."}}