{"id":"W2001106124","doi":"10.1117/12.886977","title":"Characterization of laser induced fluorescence from background aerosols in a maritime environment","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Environmental science; Aerosol; Indoor bioaerosol; Remote sensing; Lidar; Bioaerosol; Range (aeronautics); Laser-induced fluorescence; SIGNAL (programming language); False alarm; Laser; Materials science; Atmospheric sciences; Optics; Meteorology; Physics; Geology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002698139,0.0001796475,0.0002677173,0.0004526711,0.0004687436,0.0003071448,0.0002751154,0.0002451139,0.0002445982],"category_scores_gemma":[0.000233235,0.00008999699,0.0001350083,0.0002135652,0.0002017896,0.0001792256,0.0001733835,0.0002401306,0.00008277801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007232139,"about_ca_system_score_gemma":0.0005532765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02903561,"about_ca_topic_score_gemma":0.05594415,"domain_scores_codex":[0.9997578,0.00001956431,0.000005218973,0.00004579197,0.0001428952,0.00002866931],"domain_scores_gemma":[0.9998562,0.00002394296,0.00001260262,0.00000869137,0.00007752143,0.00002095219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001924378,0.00009901714,0.04728654,0.00004096925,0.00001747944,0.0001023781,0.000111945,0.001231044,0.9379102,0.00005855951,0.000105417,0.01284398],"study_design_scores_gemma":[0.00001979062,0.0007837723,0.3461191,0.00001032246,0.00003254987,0.0002465261,0.0002988729,0.01659735,0.6340814,0.00006788247,0.00171639,0.0000260027],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976016,0.0001194967,0.001760172,0.000008110916,0.000002740513,0.0000116554,0.00009153047,0.00002307436,0.0003816748],"genre_scores_gemma":[0.9939246,0.0001214942,0.004749693,0.00002256023,0.000002784485,0.00001775399,0.000357097,0.00001325626,0.0007906875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02903561,"threshold_uncertainty_score":0.05773318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02587613968380441,"score_gpt":0.2205349635506133,"score_spread":0.1946588238668089,"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."}}