{"id":"W4416952991","doi":"10.48550/arxiv.2512.00546","title":"A Graph Neural Network Approach for Localized and High-Resolution Temperature Forecasting","year":2025,"lang":"","type":"preprint","venue":"ArXiv.org","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Graph; Transfer of learning; Numerical weather prediction; Work (physics); Surface air temperature; Mean radiant temperature","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004282142,0.000672808,0.0004873586,0.0006173236,0.0003420622,0.0006378155,0.001158422,0.001003415,0.002278888],"category_scores_gemma":[0.001984487,0.0003371006,0.0004940018,0.0008246294,0.0004543315,0.0009659805,0.0006956338,0.00129946,0.0002641006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001138048,"about_ca_system_score_gemma":0.0008922215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05021091,"about_ca_topic_score_gemma":0.04961392,"domain_scores_codex":[0.9998331,0.00005709941,0.000006959138,0.00005101001,0.00002809737,0.00002376397],"domain_scores_gemma":[0.9994445,0.0003449338,0.00004766048,0.00003910313,0.00009352039,0.00003025289],"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":[0.000009413083,0.000008357172,0.0002481357,0.000005799674,0.000009505049,0.0000104905,0.000005436814,0.992945,0.0001528828,0.001367084,0.0003312911,0.004906568],"study_design_scores_gemma":[9.033548e-7,0.00000163304,0.00003603397,5.613146e-7,7.901075e-7,6.66645e-7,0.000001195576,0.9987326,0.00002191674,0.001156668,0.00004631365,8.058148e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06863697,0.0005186888,0.9240525,0.0009785937,0.0001344495,0.00004449086,0.0006391385,0.0009077447,0.004087423],"genre_scores_gemma":[0.8894002,0.0003344964,0.1051599,0.0001760117,0.0001142571,0.00009036059,0.0008307611,0.000100062,0.003794006],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05021091,"threshold_uncertainty_score":0.09983724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06845252746320202,"score_gpt":0.2457131198984298,"score_spread":0.1772605924352278,"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."}}