{"id":"W4220722235","doi":"10.18280/ria.360108","title":"Machine Learning Approaches Used for Air Quality Forecast: A Review","year":2022,"lang":"en","type":"review","venue":"Revue d intelligence artificielle","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Machine learning; Decision tree; Naive Bayes classifier; Support vector machine; Random forest; Artificial intelligence; Air quality index; Computer science; Logistic model tree; Classifier (UML); Air Pollution Index; Logistic regression; Data mining; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003953886,0.0006039583,0.001821591,0.00008182105,0.0007367114,0.00004369135,0.0009245325,0.0002101611,0.003345877],"category_scores_gemma":[0.001091906,0.0005515256,0.001091714,0.0008373224,0.0001849266,0.0001355724,0.0006104529,0.001003571,0.0006971455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000495907,"about_ca_system_score_gemma":0.00005137917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001413245,"about_ca_topic_score_gemma":0.00001872952,"domain_scores_codex":[0.99534,0.0007249786,0.001633799,0.001128564,0.0004706388,0.0007019654],"domain_scores_gemma":[0.9965034,0.001459436,0.001002702,0.0008417774,0.000012437,0.000180279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003871133,0.00009540823,0.00002017732,0.02721654,0.00003684216,0.000003429365,0.0003164877,0.003947149,3.176858e-7,0.0001855215,0.0003881732,0.9677861],"study_design_scores_gemma":[0.00002157843,0.000124935,2.775439e-7,0.008284666,0.0002753852,0.00003543853,0.0001604846,0.01460448,0.00001084416,0.0001362505,0.9757212,0.0006244802],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00000244674,0.9796741,0.01442637,0.0001149232,0.0003954854,0.001997669,0.00007555357,0.0001559488,0.003157486],"genre_scores_gemma":[0.00004153198,0.9895573,0.00157774,0.00005753341,0.0002065117,0.00115263,0.0003508851,0.0001121795,0.00694366],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.975333,"threshold_uncertainty_score":0.9996936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3351941181655919,"score_gpt":0.3760337974394479,"score_spread":0.04083967927385601,"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."}}