{"id":"W3093832362","doi":"","title":"Antecedent moisture conditions and catchment morphology as controls on spatial patterns of runoff generation in small forest catchments","year":2009,"lang":"en","type":"article","venue":"EGU General Assembly Conference Abstracts","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Antecedent moisture; Surface runoff; Hydrology (agriculture); Environmental science; Drainage basin; Storm; Ephemeral key; Water balance; Streamflow; Runoff curve number; Geology; Geography; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005399531,0.0001273633,0.0001968533,0.0007724992,0.0003109077,0.0007585258,0.0002392665,0.0001763939,0.00122329],"category_scores_gemma":[0.002449283,0.0001048967,0.0002299996,0.0009511241,0.0006609465,0.0002734116,0.0003808055,0.0001377786,0.00007914114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006042528,"about_ca_system_score_gemma":0.000427723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07497044,"about_ca_topic_score_gemma":0.1137272,"domain_scores_codex":[0.9996418,0.0001024964,0.00002021959,0.00008571419,0.00006258795,0.00008718456],"domain_scores_gemma":[0.9981839,0.0009229273,0.0003644379,0.00009100344,0.0001674129,0.0002701949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009452997,0.00001770816,0.9922287,0.000007994629,0.00004387512,0.0001079097,0.0002999104,0.0007388754,0.00398323,0.00004928836,0.00005718433,0.002370757],"study_design_scores_gemma":[9.170146e-7,0.000006762413,0.9992461,7.445584e-7,0.000003023242,0.00001232847,0.00009515232,0.0005483633,0.00004624855,0.00001363841,0.00002554955,0.000001263547],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996585,0.00001962957,0.00009436301,0.000006486183,4.146608e-7,0.000003017955,0.00007225396,0.000005608893,0.0001397975],"genre_scores_gemma":[0.9998637,0.000005651882,0.0000362855,0.000001909554,5.744888e-7,0.000001457209,0.00005658973,0.000001803792,0.00003193136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07497044,"threshold_uncertainty_score":0.1490681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01847542974104543,"score_gpt":0.2546278031576094,"score_spread":0.2361523734165639,"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."}}