{"id":"W1532904907","doi":"10.1016/s0076-6879(03)60122-9","title":"[18] Resolution in optical microscopy","year":2003,"lang":"en","type":"article","venue":"Methods in enzymology on CD-ROM/Methods in enzymology","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Optics; Microscope; Photobleaching; Microscopy; Point spread function; Resolution (logic); Optical sectioning; Materials science; Numerical aperture; Optical microscope; Light sheet fluorescence microscopy; Bright-field microscopy; Depth of focus (tectonics); 4Pi microscope; Detector; Confocal microscopy; Wavelength; Fluorescence microscope; Physics; Fluorescence; Scanning confocal electron microscopy; Scanning electron microscope; Multiphoton fluorescence microscope; Computer science","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.009965472,0.0008120131,0.001366367,0.001148637,0.0001106946,0.00002339063,0.0009493625,0.002268304,0.0001710202],"category_scores_gemma":[0.008067448,0.0008903113,0.000222401,0.001123886,0.001317948,0.00002463304,0.000411334,0.001910801,0.00002131834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004361903,"about_ca_system_score_gemma":0.0002629536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001201625,"about_ca_topic_score_gemma":0.0006308528,"domain_scores_codex":[0.9820372,0.01212801,0.001643253,0.002147865,0.0001981508,0.00184551],"domain_scores_gemma":[0.9963005,0.001535458,0.0003468736,0.001507029,0.0001131435,0.0001969877],"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":[0.0006092677,0.0006249112,0.0114645,0.00003224104,0.00002573656,0.0001995808,0.0001533608,0.0005031555,0.9643189,0.008848188,0.0004749619,0.01274521],"study_design_scores_gemma":[0.002277424,0.001550866,0.02847149,0.00009552506,0.00001873789,0.0004438293,0.0001671126,0.00008068771,0.9170004,0.02857212,0.02038345,0.0009384056],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.264946,0.002406407,0.7233539,0.0002571751,0.001475234,0.001067558,0.00001553065,0.0001079176,0.006370299],"genre_scores_gemma":[0.0447262,0.0005325169,0.9523348,0.00130361,0.000114121,0.0004220795,0.00004497527,0.0001303855,0.0003913263],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2289808,"threshold_uncertainty_score":0.9993548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.037358718324414,"score_gpt":0.4485162213472225,"score_spread":0.4111575030228085,"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."}}