{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000482881,0.0001734823,0.0001322153,0.00006529391,0.0001772884,0.0000739554,0.0001695435,0.00008657541,0.00003450546],"category_scores_gemma":[0.0002063646,0.0001291066,0.00007116275,0.0001515109,0.0005963661,0.00001344405,0.0001576038,0.00006891658,0.000017189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003867257,"about_ca_system_score_gemma":0.0001161216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008415022,"about_ca_topic_score_gemma":0.000008280985,"domain_scores_codex":[0.9981653,0.00004091694,0.0003297833,0.0008606622,0.000238945,0.0003643579],"domain_scores_gemma":[0.998504,0.00001001228,0.0002364262,0.0008347415,0.0003106069,0.0001042294],"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":[0.00002849305,0.00002436868,0.004108012,0.000003468532,0.000006405264,0.000134218,0.0000224205,0.000003969448,0.9866526,0.00001279329,0.005074098,0.003929118],"study_design_scores_gemma":[0.0001147853,0.00003875222,0.0001716163,0.00007057346,0.000006449581,0.0002156087,0.00004349353,0.00004596051,0.9782602,0.0007797231,0.02004197,0.0002108795],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9068429,0.0001998946,0.08847848,0.0001181127,0.002101521,0.000491398,0.00001731728,0.0001425753,0.001607764],"genre_scores_gemma":[0.9506118,0.00001301492,0.04467909,0.00003355768,0.00007906969,0.00001971242,0.00004695945,0.00002808344,0.004488768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04379939,"threshold_uncertainty_score":0.5264813,"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."}}