{"id":"W2022577624","doi":"10.1364/ao.43.001669","title":"Conversion of the Nikon C1 confocal laser-scanning head for multiphoton excitation on an upright microscope","year":2004,"lang":"en","type":"article","venue":"Applied Optics","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada","funders":"","keywords":"Optics; Materials science; Microscope; Confocal; Fluorescence; Laser; Two-photon excitation microscopy; Microscopy; Photon counting; Fluorescence-lifetime imaging microscopy; Confocal microscopy; Machining; Excitation; Laser scanning; Optoelectronics; Photon; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001531937,0.00163741,0.001028996,0.002203055,0.001829243,0.001238646,0.002591115,0.001575804,0.05613834],"category_scores_gemma":[0.001303218,0.001957389,0.001234516,0.000952351,0.0007762549,0.001155602,0.001490199,0.003474432,0.01686151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002360624,"about_ca_system_score_gemma":0.003026976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006203969,"about_ca_topic_score_gemma":0.01813944,"domain_scores_codex":[0.9988208,0.00007199431,0.00006561005,0.0003854555,0.0004674492,0.0001886138],"domain_scores_gemma":[0.9985733,0.0003299938,0.00007876405,0.00036879,0.0004837632,0.0001653497],"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":[0.0001872535,0.0001151135,0.0003198803,0.0004151078,0.00003335718,0.000160953,0.0001812147,0.0005191581,0.9560063,0.003782001,0.01209086,0.02618877],"study_design_scores_gemma":[0.0001182372,0.0003613213,0.005807607,0.0000756946,0.00007398656,0.001713949,0.00006944212,0.01005787,0.8107629,0.001923874,0.1687854,0.0002496449],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1164512,0.001109347,0.7890726,0.0009223525,0.001176639,0.005816408,0.008774243,0.02241035,0.05426682],"genre_scores_gemma":[0.07725644,0.001301665,0.8548136,0.0008993589,0.0001636145,0.007207101,0.008980104,0.003534622,0.04584351],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05613834,"threshold_uncertainty_score":0.1878014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01033538954021771,"score_gpt":0.289161952410025,"score_spread":0.2788265628698072,"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."}}