{"id":"W2996779126","doi":"","title":"INTEGRATED USE OF FLOW SYSTEM ANALYSIS, KARST GEOLOGY, AND REMOTE SENSING FOR HYDROGEOLOGICAL CHARACTERIZATION OF WOOD BUFFALO NATIONAL PARK, AB-NWT, CANADA","year":2014,"lang":"en","type":"article","venue":"2014 GSA Annual Meeting in Vancouver, British Columbia (19–22 October 2014)","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Karst; National park; Hydrogeology; Geology; Hydrology (agriculture); Archaeology; Forestry; Remote sensing; Geomorphology; Geography; Geotechnical engineering","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":[0.0003931807,0.000304133,0.0002768196,0.001552157,0.0006218411,0.0010666,0.0003371671,0.0001422017,0.001509894],"category_scores_gemma":[0.0007934247,0.0002174486,0.0002053837,0.001420256,0.0001942476,0.0004062614,0.0004640708,0.0002389795,0.0002783811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002527683,"about_ca_system_score_gemma":0.008117361,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8975528,"about_ca_topic_score_gemma":0.9771035,"domain_scores_codex":[0.9997473,0.00002152977,0.000009232504,0.00004516918,0.0001365034,0.0000403067],"domain_scores_gemma":[0.9995468,0.00004821007,0.00002766019,0.00001347316,0.0003147753,0.00004906678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001633981,0.0002954296,0.6501164,0.0001298621,0.0002489682,0.0001400341,0.0005456699,0.02157345,0.02232038,0.0007237229,0.007621257,0.2961214],"study_design_scores_gemma":[0.00003531168,0.00003469262,0.8490957,0.00004688185,0.0001007613,0.00005035937,0.0006643214,0.1360638,0.006506533,0.0003124384,0.007037162,0.00005209281],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9685706,0.0005388354,0.01247765,0.0003010502,0.00002997634,0.0001626663,0.005902253,0.0005752148,0.01144166],"genre_scores_gemma":[0.9587476,0.0003796319,0.03167432,0.00006050407,0.00001270419,0.00006620459,0.00392146,0.00008653147,0.005051073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1024472,"threshold_uncertainty_score":0.2061009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006826217223456274,"score_gpt":0.190554763341103,"score_spread":0.1837285461176467,"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."}}