{"id":"W4302769313","doi":"10.3791/59742-v","title":"Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements","year":2019,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Natural Sciences and Engineering Research Council of Canada","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Calibration; Uncertainty analysis; Measurement uncertainty; Software; Repeatability; Computer science; Monte Carlo method; Aerosol; Environmental science; Process engineering; Remote sensing; Simulation; Statistics; Mathematics; Physics; Engineering; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007392076,0.001470116,0.0007652066,0.005111449,0.0009325035,0.001815869,0.002278764,0.001050596,0.002772472],"category_scores_gemma":[0.02237915,0.0006991043,0.001820648,0.00294392,0.001320922,0.001984169,0.002300772,0.001897488,0.0006232731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001234352,"about_ca_system_score_gemma":0.001511329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002716691,"about_ca_topic_score_gemma":0.003226336,"domain_scores_codex":[0.9935191,0.001062175,0.0003232747,0.001118838,0.00379135,0.0001850612],"domain_scores_gemma":[0.9876384,0.006732776,0.001062028,0.002080661,0.002366851,0.0001193794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008170577,0.0005069285,0.03053028,0.001396413,0.0008408204,0.0004636066,0.001335001,0.328864,0.1311478,0.0841609,0.005638714,0.4142984],"study_design_scores_gemma":[0.00003719842,0.0001588598,0.008492882,0.0001185542,0.0001111039,0.000292852,0.0001685946,0.7866133,0.1436596,0.05034414,0.009839104,0.0001637616],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02901118,0.0002599551,0.9663678,0.00005728291,0.0000472105,0.0001144189,0.0006946338,0.00175589,0.001691594],"genre_scores_gemma":[0.3029993,0.0002656953,0.6920807,0.00008888015,0.00005067523,0.0005556669,0.001730188,0.001197742,0.001031132],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007392076,"threshold_uncertainty_score":0.03909349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02966190094646635,"score_gpt":0.3342341474957935,"score_spread":0.3045722465493271,"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."}}