{"id":"W4281389665","doi":"10.1038/s41565-022-01130-3","title":"In vivo non-invasive confocal fluorescence imaging beyond 1,700 nm using superconducting nanowire single-photon detectors","year":2022,"lang":"en","type":"article","venue":"Nature Nanotechnology","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":268,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; Fonds de recherche du Québec – Nature et technologies; National Institutes of Health","keywords":"Materials science; Fluorescence-lifetime imaging microscopy; Preclinical imaging; Two-photon excitation microscopy; Autofluorescence; Quantum dot; Microscopy; Confocal; Fluorescence; Optics; Optoelectronics; Microscope; In vivo; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002902214,0.0004144504,0.0003941906,0.0004708165,0.000379368,0.00002596744,0.0008536688,0.0009470088,0.00007181595],"category_scores_gemma":[0.0004298342,0.0004773816,0.0001295269,0.0007402914,0.0004620126,0.00003320871,0.0009723558,0.001887464,0.000001868281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003784568,"about_ca_system_score_gemma":0.00024958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009914756,"about_ca_topic_score_gemma":0.0001243815,"domain_scores_codex":[0.9973077,0.0001140237,0.0004458616,0.001049181,0.0002713572,0.0008118944],"domain_scores_gemma":[0.9988463,0.00004204467,0.0001962304,0.0007242749,0.0001214497,0.00006968686],"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":[0.0000887508,0.00008313862,0.002237618,0.00002011035,0.00001484484,0.000146091,0.0000918717,0.00007361138,0.9950756,0.0001016966,0.0003734705,0.001693169],"study_design_scores_gemma":[0.0005578236,0.0002922857,0.00001551199,0.00003965268,0.00001330484,0.0004538797,0.0006960049,0.000307714,0.9888296,0.0005326222,0.007767253,0.000494383],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933108,0.001832042,0.002852005,0.0004203884,0.0006989141,0.0005657781,0.00005953351,0.000167289,0.00009322948],"genre_scores_gemma":[0.9718186,0.00006359416,0.02683505,0.0008897356,0.0001088524,0.00009866565,0.00003493145,0.00008582151,0.00006476289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02398304,"threshold_uncertainty_score":0.9997678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006125777404353225,"score_gpt":0.2608406268168415,"score_spread":0.2547148494124883,"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."}}