{"id":"W2765723459","doi":"10.1007/s10584-017-2099-5","title":"Incorporating climate change scenarios and water-balance approach to cumulative assessment models of solution potash Mining in the Canadian Prairies","year":2017,"lang":"en","type":"article","venue":"Climatic Change","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Climate change; Water balance; Environmental science; Watershed; Water resources; Precipitation; Climate model; Water resource management; Water use; Potash; Hydrology (agriculture); Environmental resource management; Geography; Meteorology; Engineering; Geology; Computer science","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":[0.0009819558,0.0001240495,0.0001964478,0.00005976822,0.0008209066,0.0000572826,0.000264128,0.00004764249,0.000006468551],"category_scores_gemma":[0.00002400309,0.00008233956,0.00001763359,0.00005487376,0.0002970897,0.0004630541,0.0004572677,0.00008375524,0.000009993479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001100867,"about_ca_system_score_gemma":0.000003266879,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04485675,"about_ca_topic_score_gemma":0.1877941,"domain_scores_codex":[0.9989632,0.00008118627,0.0001880293,0.0002311127,0.0001637489,0.0003727552],"domain_scores_gemma":[0.9994982,0.00002865857,0.0001308431,0.0002806139,0.000006420085,0.00005529328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001589784,0.0001137692,0.8611774,0.0002344576,0.00002397315,0.00001194443,0.1306303,0.001041271,0.0000730929,0.002512556,0.000134853,0.004030467],"study_design_scores_gemma":[0.000410846,0.0001154569,0.7811897,0.0001240996,0.00003289516,0.000003284037,0.003021985,0.2117077,0.00001649026,0.003089401,0.00006319377,0.000224874],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9685087,0.00002138617,0.0002331154,0.008789485,0.00006326001,0.001101824,0.00001444311,0.00001001701,0.02125775],"genre_scores_gemma":[0.9964659,0.00001876798,0.002451418,0.0006569614,0.00002849258,0.000347773,0.00001163603,0.000006742011,0.00001227922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2106664,"threshold_uncertainty_score":0.9615036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1033188520743009,"score_gpt":0.2988704814218539,"score_spread":0.195551629347553,"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."}}