{"id":"W4416210042","doi":"10.3390/ai6110293","title":"FedEHD: Entropic High-Order Descent for Robust Federated Multi-Source Environmental Monitoring","year":2025,"lang":"en","type":"article","venue":"AI","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research","keywords":"Descent (aeronautics); Convergence (economics); Gradient descent; Calibration; Quadratic equation; Entropy (arrow of time); Term (time)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0001570403,0.000182724,0.0001581202,0.00002960206,0.0004783233,0.00008723891,0.0001704283,0.00009210139,0.0001514306],"category_scores_gemma":[0.00005557343,0.0001822423,0.00006266191,0.0001391816,0.00008938502,0.0001337837,0.0001897737,0.0001612424,0.0001363745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004476904,"about_ca_system_score_gemma":0.000009218951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003738554,"about_ca_topic_score_gemma":0.000009761292,"domain_scores_codex":[0.9987315,0.00004448488,0.0002430963,0.0003858235,0.0001881689,0.0004069233],"domain_scores_gemma":[0.9995853,0.0000749304,0.00006347294,0.0001849387,0.000005622404,0.00008572786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005961941,0.0004783235,0.7979273,0.00004917879,0.00008022692,0.000005302989,0.0007162033,0.02847715,0.03953245,0.0000482844,0.002265548,0.1303605],"study_design_scores_gemma":[0.00526002,0.0003155837,0.6386936,0.0002975504,0.0001572267,0.000007409739,0.001781573,0.1355169,0.1362215,0.0002057716,0.08020215,0.001340823],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.85386,0.00008157548,0.1439897,0.000484172,0.0008790314,0.0003587262,0.000008605783,0.0001222492,0.0002158977],"genre_scores_gemma":[0.9776565,0.000009955259,0.01639694,0.0001885865,0.0001680356,0.00005493209,0.00001427846,0.00002270174,0.005488016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1592337,"threshold_uncertainty_score":0.7431626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02349590138521913,"score_gpt":0.2627658454330765,"score_spread":0.2392699440478574,"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."}}