{"id":"W2980873209","doi":"10.1080/00102202.2019.1678837","title":"Effects of Detection Wavelengths on Soot Volume Fraction Measurements Using the Auto-Compensating LII Technique","year":2019,"lang":"en","type":"article","venue":"Combustion Science and Technology","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Soot; Incandescence; Volume fraction; Fluence; Wavelength; Volume (thermodynamics); Laser; Materials science; Analytical Chemistry (journal); Particle size; Optics; Particle (ecology); Chemistry; Combustion; Thermodynamics; Optoelectronics; Physics; 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":[0.0005207153,0.0001604782,0.0002064927,0.0006491142,0.0002444601,0.00001875512,0.0004083017,0.0002196844,0.000006502153],"category_scores_gemma":[0.001170898,0.0001304324,0.00002310144,0.001798548,0.0004957247,0.0002688788,0.0001825865,0.0004938341,0.00001250592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000262471,"about_ca_system_score_gemma":0.00004130836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007068231,"about_ca_topic_score_gemma":4.733211e-7,"domain_scores_codex":[0.99865,0.00001836095,0.0002511541,0.0003657796,0.0004231622,0.0002915672],"domain_scores_gemma":[0.9989228,0.0001243345,0.0001860215,0.0004164796,0.0003219595,0.00002840554],"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":[0.000006541925,0.00002330029,0.000439642,0.00004446972,0.00000559215,4.698626e-7,0.00001198248,0.007019166,0.9619687,0.002335083,0.000001655141,0.0281434],"study_design_scores_gemma":[0.0002172037,0.0001403755,0.0005532422,0.0001050968,0.00001196261,0.00001740247,0.0001582876,0.1654659,0.8316334,0.001482219,0.0000926642,0.0001222222],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6877584,0.00004541176,0.3106995,0.0001777677,0.0001851248,0.0004306771,3.544107e-7,0.0006028906,0.0000998086],"genre_scores_gemma":[0.994894,0.00001146541,0.004972809,0.00002038957,0.00001282154,0.00004774299,3.111102e-7,0.0000152789,0.00002519932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3071356,"threshold_uncertainty_score":0.5318879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01710774927715776,"score_gpt":0.2626997539013092,"score_spread":0.2455920046241515,"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."}}