{"id":"W4317039734","doi":"10.18280/ria.360618","title":"Exploitation of Advanced Deep Learning Methods and Feature Modeling for Air Quality Prediction","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transfer of learning; Deep learning; Artificial intelligence; Air quality index; Computer science; Feature (linguistics); Sequence (biology); Term (time); Machine learning; Dependency (UML); Encoder; Pollution; Key (lock); Air pollution; Transfer (computing); Quality (philosophy); Pattern recognition (psychology); Meteorology; Chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.001672518,0.00008520937,0.0001393976,0.00003211114,0.0004493146,0.000008195002,0.0001044707,0.0000350399,0.00008604224],"category_scores_gemma":[0.0003673922,0.00009484078,0.00005584077,0.0002071008,0.00005439259,0.0001403398,0.000134128,0.0001926957,0.000002911371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000894607,"about_ca_system_score_gemma":0.000003928434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004807952,"about_ca_topic_score_gemma":0.000003162508,"domain_scores_codex":[0.9988579,0.0002151686,0.0003178843,0.0002864395,0.0001547789,0.0001678658],"domain_scores_gemma":[0.999353,0.0002888807,0.000154833,0.0001403183,0.0000205205,0.00004243923],"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":[0.00003327467,0.00002456141,0.00102795,0.00003200542,0.000003222559,1.029555e-7,0.004080264,0.7844911,0.02282678,0.0001586925,0.000007348645,0.1873147],"study_design_scores_gemma":[0.00003949851,0.0001714213,0.0002683313,0.00001555024,0.000008880078,0.00000304,0.01528645,0.9624943,0.0188535,0.001540475,0.001221506,0.00009710788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3927374,0.0001202396,0.6064402,0.0001009592,0.0001441875,0.0001647161,0.000004878414,0.00003358782,0.0002537736],"genre_scores_gemma":[0.9307107,0.00002029894,0.06850442,0.00001395549,0.00003259708,0.00008520786,0.00001118871,0.00001174203,0.0006098591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5379733,"threshold_uncertainty_score":0.3867495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07756582339478658,"score_gpt":0.357905529071561,"score_spread":0.2803397056767744,"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."}}