{"id":"W4386127653","doi":"10.11159/icepr23.118","title":"Rasterization Of Mountain Weather Temperature Data Using Spatial Statistical Methods","year":2023,"lang":"en","type":"article","venue":"Proceedings of the World Congress on New Technologies","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Rural Development Administration","keywords":"Computer science; Meteorology; Statistical analysis; Remote sensing; Weather forecasting; Geology; Statistics; Geography; Mathematics","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":[0.0005694602,0.0003024309,0.0003718896,0.002333201,0.000292637,0.0008569113,0.0004298915,0.0001515418,0.002927858],"category_scores_gemma":[0.002623524,0.0002940928,0.0006716861,0.003915462,0.0001599438,0.000473873,0.0004220902,0.0003596053,0.0005905545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003590733,"about_ca_system_score_gemma":0.00138226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02093676,"about_ca_topic_score_gemma":0.03531244,"domain_scores_codex":[0.9996625,0.00009336254,0.00003670559,0.00005947901,0.0001173975,0.000030601],"domain_scores_gemma":[0.9989983,0.0003716916,0.00008624683,0.0001730074,0.0003507984,0.00001992389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002685498,0.0001624154,0.02061128,0.0002441757,0.0002799676,0.0001374229,0.0002482183,0.3299485,0.01376843,0.01327532,0.009980776,0.6110749],"study_design_scores_gemma":[0.00003517549,0.00003378332,0.01350939,0.00001435365,0.00004899915,0.00007178571,0.00009674953,0.9698567,0.004428443,0.004578441,0.007298077,0.00002810925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07097702,0.0002783476,0.9154027,0.0001903394,0.00006764628,0.0001031803,0.004943982,0.00604272,0.001994149],"genre_scores_gemma":[0.4150712,0.0003370171,0.5718323,0.00003858723,0.00005251863,0.0002466609,0.009867869,0.0006472451,0.001906674],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02093676,"threshold_uncertainty_score":0.04162979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03275689831927839,"score_gpt":0.3143191435046963,"score_spread":0.2815622451854179,"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."}}