{"id":"W2800433196","doi":"10.1364/cleo_at.2018.ath4o.5","title":"Combined Laser-Induced Breakdown Spectroscopy and MIR Quantum Cascade Laser Reflectance Spectroscopy for Elemental and Molecular Characterization","year":2018,"lang":"en","type":"article","venue":"Conference on Lasers and Electro-Optics","topic":"Laser-induced spectroscopy and plasma","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Quantum cascade laser; Laser-induced breakdown spectroscopy; Spectroscopy; Cascade; Laser; Materials science; Characterization (materials science); Optoelectronics; Infrared spectroscopy; Optics; Chemistry; Nanotechnology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001748734,0.0005387131,0.0005103491,0.0001610871,0.0003286771,0.0002667271,0.0001620537,0.000259794,0.00004299121],"category_scores_gemma":[0.00002969539,0.0005462414,0.00005737939,0.0002279077,0.0001788299,0.0002671896,0.00004249034,0.0003976852,0.00001205871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001009189,"about_ca_system_score_gemma":0.00007185219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001030538,"about_ca_topic_score_gemma":0.00007304938,"domain_scores_codex":[0.9978316,0.00004742352,0.0003923694,0.0006422398,0.0002223791,0.0008639461],"domain_scores_gemma":[0.999072,0.00008524908,0.0001116991,0.0003178858,0.0001090752,0.0003040491],"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":[0.0004166904,0.00006111047,0.0001102862,0.00009976746,0.00008443128,0.00001264875,0.0001827426,0.00000270056,0.986719,0.01159089,0.0002739133,0.0004458035],"study_design_scores_gemma":[0.001651336,0.002755546,0.0004392262,0.00008609499,0.0000828795,0.00002499632,0.0000706515,0.06024595,0.9311929,0.002354299,0.0005016405,0.0005944797],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935417,0.000028456,0.00291724,0.0008032717,0.0003097154,0.0006806997,0.000165974,0.0002187844,0.001334172],"genre_scores_gemma":[0.9963329,0.0008123546,0.001608984,0.0005572931,0.0002292149,0.000069911,0.0002161199,0.00008781438,0.00008544426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06024325,"threshold_uncertainty_score":0.9996989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01462161164499382,"score_gpt":0.2539258700853621,"score_spread":0.2393042584403683,"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."}}