{"id":"W2751471576","doi":"10.15353/vsnl.v1i1.40","title":"Lens-free Multi-Laser Spectral Light-Field Fusion Microscopy","year":2015,"lang":"en","type":"article","venue":"Vision Letters","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Optics; Laser; Microscopy; Lens (geology); Wavelength; Physics; Resolution (logic); Fusion; Light field; Noise (video); Materials science; Computer science; Image (mathematics); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0001506481,0.0002166379,0.0001499496,0.00006903232,0.00007434506,0.00003687429,0.0004300516,0.0001799251,0.00001909277],"category_scores_gemma":[0.0001527955,0.0001991384,0.00008997635,0.00009699709,0.00007026464,0.0000164039,0.0003062729,0.0001644876,0.00005710405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003750312,"about_ca_system_score_gemma":0.00003338068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002409725,"about_ca_topic_score_gemma":0.00001511402,"domain_scores_codex":[0.9987451,0.00004643887,0.0002115633,0.0004702155,0.0001741863,0.0003525073],"domain_scores_gemma":[0.9989755,0.000008169227,0.00007689946,0.0007456429,0.0000638682,0.0001299842],"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":[0.0001088708,0.00004718201,0.000869674,0.000004410414,0.000005907615,0.00001073945,0.00003265556,0.000009444377,0.8168703,0.000005306063,0.1814308,0.0006046193],"study_design_scores_gemma":[0.0007579731,0.0003905099,0.0002400445,0.00002913363,0.000005989188,0.00001164761,0.00002341766,0.00002934627,0.9335293,0.00003002658,0.06470952,0.0002430574],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8739363,0.0002929444,0.1175059,0.007069205,0.0004444233,0.0003005513,0.00001399537,0.000119136,0.0003175416],"genre_scores_gemma":[0.5038109,0.0002436586,0.4700237,0.02380904,0.0007901244,0.00004431548,0.0001395199,0.0001343283,0.0010045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3701254,"threshold_uncertainty_score":0.8120627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01317285824661872,"score_gpt":0.3002044050652474,"score_spread":0.2870315468186287,"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."}}