{"id":"W4405444057","doi":"10.1364/ais.2024.atu1a.3","title":"Multiple greenhouse gas sensor based on integrated photonic spectral correlation","year":2024,"lang":"en","type":"article","venue":"","topic":"Spectroscopy and Laser Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Photonics; Chip; Greenhouse gas; Range (aeronautics); Dynamic range; Electronic engineering; Integrated optics; Materials science; Optoelectronics; Environmental science; Computer science; Engineering; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000374928,0.0004908974,0.0004845806,0.0006957398,0.0003088238,0.0005751479,0.001391666,0.0009851336,0.0009987996],"category_scores_gemma":[0.0003892143,0.0004477723,0.0003038707,0.0004569841,0.0003568847,0.0009313652,0.0006103768,0.0005223358,0.0003497982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007519897,"about_ca_system_score_gemma":0.0005346518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007555618,"about_ca_topic_score_gemma":0.001698081,"domain_scores_codex":[0.9991266,0.00006925203,0.00001899606,0.0002279911,0.0004760936,0.00008118588],"domain_scores_gemma":[0.9997001,0.00006897077,0.00004513294,0.00002851226,0.0001322461,0.00002505098],"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":[0.0002361069,0.0001799379,0.001804881,0.0001520088,0.00006723653,0.0001654004,0.00004146745,0.002458494,0.9494649,0.002228523,0.0009820786,0.04221905],"study_design_scores_gemma":[0.00003038002,0.0003970142,0.002207261,0.00001427165,0.0000762047,0.0004930467,0.00002379181,0.07346895,0.9181949,0.0003686948,0.0046687,0.00005673517],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5196828,0.004201253,0.4559507,0.0006021973,0.0005479239,0.0001794525,0.0004536295,0.00374423,0.01463788],"genre_scores_gemma":[0.8314703,0.0006482474,0.1626035,0.0003257438,0.00007873432,0.00009982086,0.0002290497,0.00005505806,0.004489592],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001391666,"threshold_uncertainty_score":0.00545609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026773555166629,"score_gpt":0.248206843738396,"score_spread":0.2379391081867297,"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."}}