{"id":"W2750494147","doi":"10.22438/jeb/38/5/mrn-331","title":"Application of Soil Water Assessment Tool (SWAT) to suppress wildfire at Bayam Forest, Turkey","year":2017,"lang":"en","type":"article","venue":"Journal of Environmental Biology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Journal of Communication (Canada)","funders":"Interreg","keywords":"Environmental science; Soil and Water Assessment Tool; SWAT model; Hydrology (agriculture); Watershed; Soil water; STREAMS; Water resource management; Water resources; Sustainability; Digital elevation model; Streamflow; Geography; Soil science; Remote sensing; Ecology; Drainage basin; Computer science; Geology; Cartography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000384272,0.0001585344,0.0002956097,0.00004466963,0.0003336984,0.00001092451,0.0005466181,0.0001012179,0.0005881014],"category_scores_gemma":[0.00001232102,0.000105727,0.0001086052,0.00001354253,0.0005361455,0.0002036982,0.001066006,0.0001311307,0.0002462223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002038907,"about_ca_system_score_gemma":0.000002039221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008446662,"about_ca_topic_score_gemma":0.00004518185,"domain_scores_codex":[0.9988351,0.00006431154,0.0004150755,0.0002354616,0.0001577415,0.0002922676],"domain_scores_gemma":[0.9991277,0.00002648943,0.0003683403,0.0003942067,0.000002112619,0.00008115103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001096144,0.000151866,0.7682819,0.000004171495,0.00007994051,0.000008068298,0.0001853032,0.002105907,0.2244262,0.00002548489,0.001075988,0.003545618],"study_design_scores_gemma":[0.0006679015,0.0005482384,0.9463593,0.000005803829,0.00005730144,0.0000233278,0.00004746843,0.0002431784,0.02061899,0.000742522,0.03052547,0.0001604393],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951464,0.00002038955,0.0006902724,0.001669738,0.0002057018,0.0002075908,0.0000127726,0.000003956766,0.002043176],"genre_scores_gemma":[0.9984334,0.00009973813,0.0006120328,0.0002869638,0.00006629762,0.00001543769,0.00001103161,0.000009897884,0.0004652625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2038072,"threshold_uncertainty_score":0.6439298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005822224466248472,"score_gpt":0.2406723711035071,"score_spread":0.2348501466372587,"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."}}