{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006092925,0.0007846498,0.0004882924,0.0004645933,0.0001576672,0.0005036576,0.0007961908,0.000652871,0.001149334],"category_scores_gemma":[0.001548015,0.0003160971,0.0006748906,0.0006383933,0.000260309,0.001114949,0.0008737427,0.001421417,0.0003931187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005017443,"about_ca_system_score_gemma":0.0007427711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006584021,"about_ca_topic_score_gemma":0.00612771,"domain_scores_codex":[0.9997718,0.00004547176,0.00001630156,0.00006767942,0.00006893863,0.00002988422],"domain_scores_gemma":[0.9996389,0.000153621,0.00004061316,0.00004441084,0.0001057064,0.00001669551],"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":[0.00007245757,0.00009763379,0.002251047,0.0001069179,0.0001091323,0.00008267018,0.00003579989,0.6774206,0.006638807,0.006758279,0.002507333,0.3039193],"study_design_scores_gemma":[0.000001270641,0.00000629509,0.00008360053,0.000002308938,0.00000327377,0.000003875227,0.000001152885,0.997964,0.0004543992,0.001259814,0.0002184075,0.000001662333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02042987,0.001158938,0.9759375,0.0002953448,0.00008668956,0.00001985113,0.0001744721,0.0006804527,0.001216869],"genre_scores_gemma":[0.8135567,0.001909912,0.1788162,0.0002846676,0.0001347597,0.0001080934,0.0008740537,0.00008758665,0.004228042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006584021,"threshold_uncertainty_score":0.01309139,"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."}}