{"id":"W4391578869","doi":"10.1117/1.nph.11.s1.s11503","title":"Photonic neural probe enabled microendoscopes for light-sheet light-field computational fluorescence brain imaging","year":2024,"lang":"en","type":"article","venue":"Neurophotonics","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Max-Planck-Gesellschaft","keywords":"Light sheet fluorescence microscopy; Fluorescence-lifetime imaging microscopy; Materials science; Fluorescence; Optics; Microscopy; Light field; Optical fiber; Fluorescence microscope; Bright-field microscopy; Physics","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"],"consensus_categories":[],"category_scores_codex":[0.0001612176,0.000362422,0.0002484712,0.0001142495,0.0001810369,0.0001953074,0.0004764505,0.0001335933,0.00002216644],"category_scores_gemma":[0.0002152892,0.0003571684,0.0002086216,0.0002237261,0.00007501874,0.00002631654,0.0002210098,0.000301807,0.00001639511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004603678,"about_ca_system_score_gemma":0.000227656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007028319,"about_ca_topic_score_gemma":0.000005988004,"domain_scores_codex":[0.9978266,0.00006145173,0.0003731948,0.0009709499,0.0001892285,0.0005785735],"domain_scores_gemma":[0.999051,0.0001010634,0.00008331452,0.0004955995,0.0001536819,0.0001153686],"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":[0.0001368674,0.00004568372,0.00007709145,0.0001234016,0.00002224436,0.00004910792,0.00006005589,0.0001739868,0.9768443,0.0001934097,0.02001668,0.002257221],"study_design_scores_gemma":[0.0003046687,0.000346903,0.0000126008,0.00007996433,0.00001918576,0.000090852,0.00001012424,0.01609155,0.8108058,0.0004686026,0.1714703,0.0002994428],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5657312,0.01914433,0.3780111,0.02224911,0.004160922,0.006943578,0.0004154859,0.001779709,0.001564607],"genre_scores_gemma":[0.7444835,0.0006420012,0.2429832,0.008482432,0.0005598065,0.0006716385,0.0003788115,0.0003650197,0.001433615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1787523,"threshold_uncertainty_score":0.999888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006218867718675932,"score_gpt":0.2726861708940301,"score_spread":0.2664673031753542,"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."}}