{"id":"W7100233250","doi":"","title":"The Marmot and Streeter Exper~ental Basin Programs","year":2016,"lang":"en","type":"article","venue":"","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Marmot; Watershed; Hydrology (agriculture); Watershed management; Structural basin; Drainage basin; Water supply; Streamflow; Water balance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001039259,0.0002175353,0.0001921425,0.0007729789,0.003111964,0.001068022,0.0008879564,0.0004867825,0.01591425],"category_scores_gemma":[0.001521638,0.0003370037,0.0002467372,0.000837143,0.0008791303,0.0005848221,0.001685937,0.0006813194,0.0008676597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008064932,"about_ca_system_score_gemma":0.03029272,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6977978,"about_ca_topic_score_gemma":0.9327911,"domain_scores_codex":[0.9991716,0.00008503359,0.00001109032,0.0001108743,0.0003486925,0.0002728103],"domain_scores_gemma":[0.9987583,0.000138183,0.0000700633,0.00009262902,0.0004127562,0.000528076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001430686,0.0009216379,0.1721972,0.0002588578,0.000172752,0.002182019,0.005262845,0.003303979,0.01324842,0.1040635,0.1784208,0.5185373],"study_design_scores_gemma":[0.0001202825,0.0003032202,0.3608345,0.0001087467,0.0000543705,0.0002540443,0.002445134,0.003011714,0.003932022,0.002647978,0.6262378,0.00005021271],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.478015,0.002430234,0.005947785,0.008324318,0.0002962945,0.001328308,0.009739773,0.0008604636,0.4930578],"genre_scores_gemma":[0.5191075,0.001448774,0.02127996,0.002377198,0.00004922757,0.0005507905,0.004607652,0.0001123521,0.4504665],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6977978,"threshold_uncertainty_score":0.6079639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007309763231905061,"score_gpt":0.1961232830940644,"score_spread":0.1888135198621593,"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."}}