{"id":"W2116423861","doi":"10.1007/s00340-005-2008-x","title":"Remote sensing of pollutants using femtosecond laser pulse fluorescence spectroscopy","year":2005,"lang":"en","type":"article","venue":"Applied Physics B","topic":"Spectroscopy and Laser Applications","field":"Chemistry","cited_by":109,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Femtosecond; Fluorescence; Materials science; Quantum optics; Laser-induced fluorescence; Laser; Lidar; Optics; Spectroscopy; Fluorescence spectroscopy; Pulse (music); Molecule; Remote sensing; Pollutant; Physics; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000584537,0.0002128702,0.000259502,0.0000271846,0.0001366154,0.00002700206,0.0002090082,0.00009058311,0.0005766249],"category_scores_gemma":[0.000004449493,0.0002370048,0.00008091449,0.0002567158,0.0001123361,0.00008272423,0.00006171852,0.0002385774,0.00007795055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001024818,"about_ca_system_score_gemma":0.00006989074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006200957,"about_ca_topic_score_gemma":0.00001500016,"domain_scores_codex":[0.9987626,0.000005876451,0.0002922326,0.0003641075,0.0002158278,0.0003593255],"domain_scores_gemma":[0.999042,0.00004935219,0.000177248,0.0006037409,0.0000368568,0.00009078056],"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":[0.00003424057,0.0000545501,0.00001708402,0.00003297367,0.00002928792,9.676293e-7,0.0001636889,0.000629464,0.9645128,0.0019866,0.00006935537,0.03246894],"study_design_scores_gemma":[0.000355178,0.000004412372,0.0000364011,0.00002866222,0.00004291796,0.0000040273,0.00007606662,0.03023397,0.9640449,0.004449671,0.0005040703,0.0002197678],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9224737,0.00003316028,0.01791616,0.00005649007,0.0000321341,0.0001299987,0.00008674114,0.0001063275,0.05916534],"genre_scores_gemma":[0.9572936,0.000009959246,0.04185067,0.0001249175,0.0005290515,0.0000011161,0.0000177456,0.0000429242,0.0001299877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05903535,"threshold_uncertainty_score":0.9664775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01564753767954933,"score_gpt":0.2662118269149965,"score_spread":0.2505642892354472,"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."}}