{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001764698,0.001443714,0.001986381,0.003965976,0.0003614958,0.00157948,0.001837897,0.001560516,0.003529137],"category_scores_gemma":[0.004276671,0.0005607009,0.001346844,0.006493217,0.0005491085,0.002287641,0.0006750933,0.001750024,0.002202892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007894841,"about_ca_system_score_gemma":0.001608172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003193623,"about_ca_topic_score_gemma":0.002553638,"domain_scores_codex":[0.9992452,0.0001478691,0.0001245456,0.0001549788,0.0002900343,0.00003734447],"domain_scores_gemma":[0.99685,0.002155746,0.0001864308,0.00008828383,0.000666605,0.00005289859],"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":[0.00004931235,0.00008097825,0.0004867428,0.02112808,0.0001887927,0.00009932484,0.00006054703,0.002160317,0.0004632114,0.004063862,0.01665565,0.9545631],"study_design_scores_gemma":[0.00002825669,0.0002464431,0.003220157,0.02018216,0.0006596677,0.001090186,0.0001544747,0.003596417,0.001161966,0.00876038,0.9607813,0.0001186482],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001809931,0.996868,0.001490565,0.0002585414,0.0002490348,0.00001079858,0.00003762877,0.00001949139,0.0008849076],"genre_scores_gemma":[0.001413367,0.9963742,0.001447208,0.0001166741,0.0002664335,0.00001432275,0.00006652224,0.000005309412,0.0002959592],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003965976,"threshold_uncertainty_score":0.01180613,"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."}}