{"id":"W3212384989","doi":"10.1088/1361-6501/ac370b","title":"A layer-peeling method for signal trapping correction in planar LII measurements of statistically steady flames","year":2021,"lang":"en","type":"article","venue":"Measurement Science and Technology","topic":"Combustion and flame dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; Comisión Nacional de Investigación Científica y Tecnológica","keywords":"Soot; Laminar flow; Materials science; Volume fraction; Planar; Trapping; Diffusion flame; Diffusion; Analytical Chemistry (journal); Optics; SIGNAL (programming language); Volume (thermodynamics); Mechanics; Combustion; Chemistry; Physics; Thermodynamics; Composite material; Chromatography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001948226,0.00009181032,0.0001764308,0.0004348263,0.0000804123,0.0000211378,0.0001225622,0.00007340872,0.000006284966],"category_scores_gemma":[0.0006576402,0.0000977028,0.00001617498,0.0009329462,0.0001206324,0.00007969417,0.00002095313,0.0001268732,5.686289e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002083098,"about_ca_system_score_gemma":0.0001731286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008412302,"about_ca_topic_score_gemma":0.0002928866,"domain_scores_codex":[0.9987156,0.00001939738,0.0002530257,0.0002260892,0.0005425808,0.0002433458],"domain_scores_gemma":[0.9990674,0.00003990094,0.00003537928,0.0001202953,0.000700697,0.00003629165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001153268,0.00004577335,0.003653311,0.00007618439,0.00001934247,0.000002993531,0.0001164455,0.003521922,0.8678064,0.002140715,0.0001103371,0.122495],"study_design_scores_gemma":[0.0008948319,0.000133468,0.002901568,0.000179454,0.00002804286,0.00001816988,0.001047432,0.6177729,0.3741511,0.002086382,0.0005612662,0.0002254694],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04983951,0.0003175592,0.9479099,0.0003708739,0.0004155177,0.0002631322,0.000005937301,0.0001449507,0.0007325966],"genre_scores_gemma":[0.9719267,0.00002036618,0.02798339,0.00001635261,0.000007597333,0.00002702437,0.000001463132,0.000007668332,0.000009464482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9220872,"threshold_uncertainty_score":0.3984205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04510723883372492,"score_gpt":0.2778886214497386,"score_spread":0.2327813826160137,"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."}}