{"id":"W4255089263","doi":"10.15278/isms.2021.fe09","title":"HIGH ACCURACY NEAR-INFRARED CARBON DIOXIDE INTENSITY MEASUREMENTS TO SUPPORT REMOTE SENSING","year":2021,"lang":"en","type":"article","venue":"Proceedings of the 2021 International Symposium on Molecular Spectroscopy","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Carbon dioxide; Remote sensing; Intensity (physics); Infrared; Carbon dioxide sensor; Environmental science; Materials science; Computer science; Optics; Geology; Chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007901272,0.0005605951,0.0003227942,0.0007775886,0.0005780245,0.0005959101,0.001334657,0.0006057004,0.002486174],"category_scores_gemma":[0.00175562,0.0002892196,0.000214704,0.0009072384,0.0002507867,0.0008752847,0.0007443317,0.0006022198,0.0009394868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000811526,"about_ca_system_score_gemma":0.0006826665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006891707,"about_ca_topic_score_gemma":0.01539501,"domain_scores_codex":[0.9990168,0.0000667811,0.00003001549,0.0002744113,0.0005469556,0.00006506518],"domain_scores_gemma":[0.9993325,0.0000989532,0.00006982134,0.0001545628,0.0003200585,0.00002405838],"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":[0.0002948826,0.0005750388,0.04941043,0.0001667392,0.0000980011,0.0002305246,0.0001954653,0.04773183,0.7924491,0.004019524,0.006341339,0.09848716],"study_design_scores_gemma":[0.00005564401,0.0001307445,0.03793977,0.00002042349,0.00004783967,0.0001347554,0.0000531509,0.3653227,0.5819498,0.001085038,0.01317778,0.00008229229],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5904257,0.0003473696,0.3774861,0.0003569077,0.0002195407,0.0003582268,0.007575331,0.006556225,0.01667468],"genre_scores_gemma":[0.6649249,0.00009434834,0.3294115,0.0001898991,0.00005089963,0.0002093928,0.003138463,0.0003726766,0.001608071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006891707,"threshold_uncertainty_score":0.01370317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00965214591542224,"score_gpt":0.2400564267791911,"score_spread":0.2304042808637688,"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."}}