{"id":"W3199547357","doi":"10.3390/chemosensors9090268","title":"Non-Local Patch Regression Algorithm-Enhanced Differential Photoacoustic Methodology for Highly Sensitive Trace Gas Detection","year":2021,"lang":"en","type":"article","venue":"Chemosensors","topic":"Spectroscopy and Laser Applications","field":"Chemistry","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Basic and Applied Basic Research Foundation of Guangdong Province; China Postdoctoral Science Foundation; Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities; Recruitment Program of Global Experts; National Science Foundation","keywords":"Trace gas; Noise (video); Noise reduction; Signal-to-noise ratio (imaging); Analytical Chemistry (journal); Absorption (acoustics); Energy (signal processing); Materials science; Wavelet; Spectral line; Algorithm; Optics; Physics; Acoustics; Mathematics; Chemistry; Computer science; Artificial intelligence; Statistics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001040844,0.0002665404,0.0003741173,0.00003762302,0.0002507164,0.00003210891,0.0001111989,0.0003309216,0.0003368177],"category_scores_gemma":[0.0001409605,0.0002621458,0.0001951289,0.0001947647,0.0001155966,0.00005288924,0.00004542881,0.0003157996,0.00002277781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001514714,"about_ca_system_score_gemma":0.00006735152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004733408,"about_ca_topic_score_gemma":0.00003679638,"domain_scores_codex":[0.9984421,0.00004923839,0.0002915938,0.00063926,0.000169907,0.0004079231],"domain_scores_gemma":[0.998619,0.0004660485,0.0001416405,0.0004230213,0.0002229809,0.0001273709],"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":[0.0001330294,0.0001183764,0.000004501472,0.00007554906,0.00006637534,0.000012271,0.0003306885,0.00006182549,0.9632522,0.00001328215,0.000192409,0.03573948],"study_design_scores_gemma":[0.001025693,0.00003164372,0.00007014436,0.00004209126,0.0001467548,0.00006243473,0.001568335,0.04742745,0.9483218,0.0003965751,0.000637457,0.0002696628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.553077,0.0000253259,0.445891,0.0001064785,0.0001396579,0.0001236204,0.0000547679,0.00009916418,0.0004829639],"genre_scores_gemma":[0.9798872,0.00004134684,0.01682679,0.00006474993,0.0004421235,0.0002137577,0.000170054,0.00005240643,0.002301539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4290642,"threshold_uncertainty_score":0.9999831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02104329993885586,"score_gpt":0.2963044479649069,"score_spread":0.2752611480260511,"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."}}