{"id":"W1980698430","doi":"10.1016/j.bpj.2009.09.038","title":"Subdiffraction-Limit Two-Photon Fluorescence Microscopy for GFP-Tagged Cell Imaging","year":2009,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microscopy; Photobleaching; Fluorescence microscope; Microscope; Photoactivated localization microscopy; Two-photon excitation microscopy; Resolution (logic); Fluorescence; Optics; Super-resolution microscopy; Optical microscope; Point spread function; Materials science; 4Pi microscope; Physics; Scanning electron microscope; Multiphoton fluorescence microscope","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":[0.001052617,0.0004145259,0.0006274981,0.0005182521,0.0006722481,0.0009114987,0.001758744,0.001117853,0.002562269],"category_scores_gemma":[0.001725201,0.0005768525,0.0002592131,0.0005313929,0.0009238208,0.001756974,0.001164115,0.002025666,0.0009221468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001952542,"about_ca_system_score_gemma":0.0006295086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008368958,"about_ca_topic_score_gemma":0.002175268,"domain_scores_codex":[0.9993259,0.0001005944,0.00004142664,0.0001388427,0.0003381842,0.00005510538],"domain_scores_gemma":[0.9985774,0.000667977,0.0001225284,0.0003342342,0.0002042396,0.00009369418],"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":[0.0001172355,0.00005320577,0.0002440243,0.000132614,0.000007014009,0.00006770045,0.0001141063,0.0009571388,0.9809523,0.006693156,0.0008159915,0.009845436],"study_design_scores_gemma":[0.00002634903,0.00004016862,0.001608874,0.00003469756,0.00000779642,0.0003858536,0.00003343738,0.07655279,0.909925,0.004394609,0.00694173,0.0000486971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3708599,0.002095666,0.6177412,0.0007589101,0.00006730438,0.0001981741,0.0003755814,0.00187931,0.006023962],"genre_scores_gemma":[0.7015655,0.001542329,0.2884817,0.000346689,0.00004217077,0.0006257649,0.0005443544,0.0004591751,0.00639231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002562269,"threshold_uncertainty_score":0.01416677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007120523792291807,"score_gpt":0.296741596176581,"score_spread":0.2896210723842891,"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."}}