{"id":"W2802888411","doi":"10.1080/10962247.2018.1469555","title":"Analysis of the number of flux chamber samples and study area size on the accuracy of emission rate measurements","year":2018,"lang":"en","type":"article","venue":"Journal of the Air & Waste Management Association","topic":"Landfill Environmental Impact Studies","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Golder Associates (Canada)","funders":"","keywords":"Monte Carlo method; Flux (metallurgy); Sampling (signal processing); Standard deviation; Environmental science; Population; Statistics; Accuracy and precision; Mathematics; Physics; Materials science; Optics","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":[0.03151991,0.0007066709,0.001160593,0.001074087,0.000621476,0.001472456,0.001357805,0.001302706,0.000954628],"category_scores_gemma":[0.1229857,0.0007928983,0.001552141,0.001330446,0.0009993246,0.001850276,0.0008276267,0.001046107,0.0001530273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001511907,"about_ca_system_score_gemma":0.001293914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004862521,"about_ca_topic_score_gemma":0.005125766,"domain_scores_codex":[0.9814941,0.01146826,0.001041211,0.002228369,0.003071105,0.0006969853],"domain_scores_gemma":[0.5586481,0.4133561,0.009135797,0.008686665,0.00959984,0.0005735878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001496275,0.0002786923,0.1844255,0.0003036215,0.0005723952,0.0003403828,0.0004092009,0.7617361,0.01008896,0.00397867,0.0005414408,0.03582871],"study_design_scores_gemma":[0.00008401608,0.000782711,0.08969448,0.00008933884,0.0003459177,0.000379859,0.0002560249,0.8867321,0.0177576,0.002140426,0.001629862,0.0001075453],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8718659,0.0007885185,0.1232538,0.0002942296,0.00003764233,0.000256879,0.0005156737,0.0003472578,0.002640099],"genre_scores_gemma":[0.9613494,0.0001652439,0.03720479,0.0000699439,0.00001097233,0.0002166523,0.0004453652,0.00008402384,0.0004536294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03151991,"threshold_uncertainty_score":0.1666952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02918055255114897,"score_gpt":0.2649099544586332,"score_spread":0.2357294019074842,"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."}}