{"id":"W2399610593","doi":"10.4236/jep.2016.76080","title":"Optimization of Air Quality Monitoring Network Using GIS Based Interpolation Techniques","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Protection","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"King Abdulaziz City for Science and Technology","keywords":"Interpolation (computer graphics); Mean squared error; Correlation coefficient; Mean absolute percentage error; Data mining; Multivariate interpolation; Computer science; Process (computing); Geographic information system; Data quality; Algorithm; Statistics; Remote sensing; Mathematics; Engineering; Geography; Artificial intelligence","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":[0.001261105,0.0008582838,0.0006076258,0.001201975,0.0003869383,0.0005263998,0.0006310497,0.0003181581,0.000906444],"category_scores_gemma":[0.002161406,0.0003566381,0.0005856907,0.001420933,0.0002416978,0.000631808,0.0005135204,0.0003896592,0.0002059226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006670633,"about_ca_system_score_gemma":0.0009895208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007084065,"about_ca_topic_score_gemma":0.006669007,"domain_scores_codex":[0.9992535,0.0002790644,0.00004236612,0.0001310944,0.0002504198,0.00004358484],"domain_scores_gemma":[0.9993734,0.0002915953,0.0001114341,0.00004627504,0.0001618399,0.00001559838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006096958,0.00004966587,0.003750853,0.00008460156,0.00004427572,0.00004617049,0.00006425488,0.9161843,0.00476749,0.001433331,0.0002870847,0.07322698],"study_design_scores_gemma":[0.00001087031,0.00005232289,0.001419406,0.000007168356,0.00001360961,0.00002571755,0.0000272156,0.9938625,0.002715987,0.0007917277,0.001064425,0.000009064451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05596096,0.0001589681,0.941164,0.00006119955,0.00002169225,0.00009719141,0.0001343564,0.0006939564,0.001707625],"genre_scores_gemma":[0.4266353,0.0001802594,0.5715529,0.00001666381,0.00001154883,0.0002355832,0.000361498,0.00005826306,0.0009479498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007084065,"threshold_uncertainty_score":0.01408565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05535537500933596,"score_gpt":0.3171614509276117,"score_spread":0.2618060759182758,"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."}}