{"id":"W2980970255","doi":"10.5194/isprs-archives-xlii-4-w18-117-2019","title":"HOW WILL CLIMATE CHANGE IMPACT THE STORM MAGNITUDE AND THROUFALL IN SEVERAL FOREST AREAS IN IRAN?","year":2019,"lang":"en","type":"article","venue":"˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"Iran National Science Foundation; Sleep Research Society Foundation; Chinese Academy of Sciences; National Science Foundation","keywords":"Environmental science; Climate change; Coupled model intercomparison project; Storm; Precipitation; Atmospheric sciences; Sensitivity (control systems); Climate sensitivity; Representative Concentration Pathways; Climatology; Climate model; Meteorology; Geography; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006510607,0.0002668147,0.0002257631,0.0008131597,0.00041053,0.0006309093,0.000376119,0.0003144961,0.0009980216],"category_scores_gemma":[0.001231219,0.0001267751,0.0005138509,0.00140724,0.0003132504,0.00077012,0.0003655939,0.0003853049,0.0001446814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001641792,"about_ca_system_score_gemma":0.0009394058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06226852,"about_ca_topic_score_gemma":0.0756301,"domain_scores_codex":[0.9996974,0.0000595592,0.00001655157,0.00006616714,0.0000639456,0.00009625351],"domain_scores_gemma":[0.9995487,0.00006748362,0.0001351644,0.00002718785,0.0001845006,0.00003696338],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001151911,0.0000528186,0.9579222,0.00007881124,0.0001452884,0.0004873431,0.0006548254,0.01081592,0.001289363,0.0008069386,0.002256574,0.02537478],"study_design_scores_gemma":[0.000009561273,0.00003110381,0.9838134,0.00002164245,0.00007698773,0.0001347042,0.001548612,0.01072125,0.0005566367,0.0006868497,0.002379202,0.00002008211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995237,0.0003749814,0.0006003907,0.0007220085,0.00003365018,0.00001298449,0.001064484,0.00002650586,0.001927981],"genre_scores_gemma":[0.9986718,0.0001996123,0.0002921293,0.00004408647,0.00002060309,0.000005439071,0.0005912458,0.000004499466,0.0001707593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06226852,"threshold_uncertainty_score":0.1238121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01432095636874233,"score_gpt":0.2376320926246273,"score_spread":0.2233111362558849,"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."}}