{"id":"W2975444001","doi":"10.4236/gep.2019.79012","title":"Climate Change Predictions of Increased Watershed Flow in Atlantic Canada: Implications for Surface Water Vulnerability and Ameliorative Land Use Planning and Management","year":2019,"lang":"en","type":"article","venue":"Journal of Geoscience and Environment Protection","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Agriculture and Agri-Food Canada","keywords":"Environmental science; Watershed; Watershed management; Hydrology (agriculture); Surface runoff; Climate change; Land use, land-use change and forestry; Land use; Riparian zone; Streamflow; Ecohydrology; Wetland; Water resource management; Geography; Drainage basin; Ecosystem; Ecology; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0004972779,0.00007936823,0.000136779,0.00004739263,0.0001596706,0.00001473522,0.00004453759,0.0000267223,0.00001079745],"category_scores_gemma":[0.00000601211,0.00005508351,0.00001250707,0.00005012683,0.000151207,0.0004055022,0.0001178914,0.00006766127,5.374382e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007547082,"about_ca_system_score_gemma":0.000002169713,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01423137,"about_ca_topic_score_gemma":0.004496699,"domain_scores_codex":[0.999306,0.00004269717,0.0002030547,0.0001795359,0.000104523,0.0001642421],"domain_scores_gemma":[0.9997623,0.00002407275,0.00009827413,0.00006978954,0.000004051075,0.00004151534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008963021,0.00003799227,0.9898769,0.00005497238,0.00001275995,0.000001239957,0.0006937341,0.004429841,0.003382809,0.000007026359,0.000007388519,0.001405729],"study_design_scores_gemma":[0.0004951873,0.0002199281,0.9935951,0.00002974189,0.00002760187,0.000007827495,0.0001976387,0.004529813,0.000309459,0.0001760831,0.000345214,0.00006643233],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965551,0.00002684266,0.001689104,0.001025285,0.00003529517,0.0006447691,0.000007385569,0.000002119152,0.00001413655],"genre_scores_gemma":[0.9986391,0.0005181984,0.0007240326,0.00004720139,0.000006475221,0.00003282407,0.000002051773,0.000002763178,0.00002731731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009734671,"threshold_uncertainty_score":0.9923329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02199052144172442,"score_gpt":0.2224163176628388,"score_spread":0.2004257962211144,"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."}}