{"id":"W2083005216","doi":"10.1002/hyp.1038","title":"Using numerical modelling to address hydrologic forest management issues in British Columbia","year":2001,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Hydrological modelling; Watershed; Context (archaeology); Forest management; Watershed management; Environmental resource management; Environmental science; Data collection; Computer science; Data management; Hydrology (agriculture); Geography; Data mining; Engineering; Geology; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003331777,0.0001971834,0.000359544,0.00005236859,0.0003323058,0.0001353182,0.0004548851,0.0001453021,0.001468702],"category_scores_gemma":[0.00006345664,0.0002384723,0.00004835475,0.0007931508,0.0002542154,0.0002502208,0.0007368044,0.0001997575,0.0003397964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009011526,"about_ca_system_score_gemma":0.00000336999,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007889944,"about_ca_topic_score_gemma":0.01789922,"domain_scores_codex":[0.9977058,0.00008585879,0.0003565655,0.0007848426,0.0003034079,0.0007635058],"domain_scores_gemma":[0.9995199,0.00005772066,0.00006551774,0.0002100738,0.00001081902,0.0001359478],"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":[0.00003280707,0.0001925304,0.404636,0.00002748541,0.00001469289,0.0004842327,0.00007592837,0.5932359,0.000006659085,0.000007312864,0.0008274472,0.0004590371],"study_design_scores_gemma":[0.002378277,0.001281777,0.205921,0.0002200729,0.0001774671,0.0002564241,0.000411694,0.6321279,0.00003376441,0.05088471,0.1041081,0.002198806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757261,0.0002128754,0.01155846,0.0008831965,0.00006031075,0.0005723835,0.000002061809,0.0001488925,0.01083568],"genre_scores_gemma":[0.9924219,0.00048288,0.003657518,0.001949855,0.00004312704,0.0001451301,0.000005323885,0.0000170329,0.001277246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.198715,"threshold_uncertainty_score":0.9994441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03890981643226685,"score_gpt":0.2633063410308456,"score_spread":0.2243965245985788,"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."}}