{"id":"W4382066226","doi":"10.3390/su151310020","title":"Optimizing Regression Models for Predicting Noise Pollution Caused by Road Traffic","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Noise Effects and Management","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Qassim University","keywords":"Mean squared error; Noise (video); Kriging; Hyperparameter; Regression; Regression analysis; Support vector machine; Noise pollution; Computer science; Pollution; Statistics; Predictive modelling; Mathematics; Machine learning; Artificial intelligence; Noise reduction","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002639795,0.0001979634,0.0002853094,0.0001404653,0.001330583,0.000017424,0.0001604349,0.0001965693,0.00002898832],"category_scores_gemma":[0.001255481,0.0001639803,0.0001154909,0.0004263939,0.00005295947,0.0002673503,0.0002106564,0.0003305994,0.0000159564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0013115,"about_ca_system_score_gemma":0.0003882708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002672812,"about_ca_topic_score_gemma":0.00004705118,"domain_scores_codex":[0.9973712,0.000484907,0.000480345,0.0005110393,0.0002513551,0.0009011665],"domain_scores_gemma":[0.9983358,0.0003930193,0.0001867172,0.0004757665,0.0004533964,0.0001553457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001404459,0.0007163066,0.006283027,0.01726949,0.0001875565,0.00003624013,0.045005,0.3131334,0.002488504,0.01183958,0.4324211,0.1692153],"study_design_scores_gemma":[0.005292248,0.0004695978,0.01678221,0.000564827,0.000147862,2.247127e-7,0.04365436,0.8739564,0.00016009,0.02327796,0.03494944,0.0007447766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971383,0.0001279379,0.01212957,0.007527845,0.0008200922,0.006250098,0.00007158449,0.0009980367,0.0006918891],"genre_scores_gemma":[0.9923311,0.00002087732,0.000249357,0.0002337885,0.0001950092,0.001336341,0.0001126343,0.00004059571,0.005480316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.560823,"threshold_uncertainty_score":0.9999695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03436818284546374,"score_gpt":0.3856380421691437,"score_spread":0.3512698593236799,"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."}}