{"id":"W2086874125","doi":"10.1139/x03-213","title":"The effects of spatial aggregation of complex topography on hydroecological process simulations within a rugged forest landscape: development and application of a satellite-based topoclimatic model","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Korea Science and Engineering Foundation; Ministry of Environment","keywords":"Environmental science; Evapotranspiration; Spatial variability; Spatial ecology; Satellite; Digital elevation model; Temporal scales; Spatial analysis; Atmospheric sciences; Remote sensing; Hydrology (agriculture); Ecology; Geology; Mathematics; Statistics","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":[0.0007786694,0.0003888918,0.0004137186,0.0002759987,0.000378302,0.0007908496,0.0005217047,0.0005081178,0.0003296596],"category_scores_gemma":[0.003011849,0.0003263935,0.0004517117,0.0003779969,0.000590142,0.0006192441,0.0007135774,0.000411298,0.00005070275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00105291,"about_ca_system_score_gemma":0.0006527975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03718457,"about_ca_topic_score_gemma":0.02669367,"domain_scores_codex":[0.9997519,0.0001098669,0.00001976201,0.00004873228,0.00003620173,0.00003347516],"domain_scores_gemma":[0.998577,0.0008371705,0.0001765396,0.0001881471,0.0001271547,0.00009406203],"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":[0.00003749247,0.00003670207,0.01354988,0.000006291721,0.0000303276,0.00004567302,0.00004777854,0.9823905,0.00101659,0.0001862865,0.00002422739,0.00262826],"study_design_scores_gemma":[0.00001108,0.00002478243,0.003354325,0.000001725481,0.000009622061,0.000007707918,0.00002101427,0.9959406,0.0004695406,0.0001114923,0.00004344671,0.000004661505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964142,0.00001842221,0.003126929,0.0000364056,0.000002462334,0.00001115798,0.00003830872,0.00004847676,0.0003036187],"genre_scores_gemma":[0.9956115,0.0000231649,0.004247804,0.000009692272,0.000001783028,0.00001087318,0.00003453805,0.000007686165,0.00005307512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03718457,"threshold_uncertainty_score":0.07393628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01726086509778488,"score_gpt":0.2649901994840268,"score_spread":0.2477293343862419,"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."}}