{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009637383,0.0002419871,0.0009290015,0.0002747686,0.00013642,0.0001132328,0.0001929471,0.0002352211,0.00005078973],"category_scores_gemma":[0.0009009928,0.0003461378,0.0001733068,0.0007066739,0.0001392751,0.0002843522,0.00007161893,0.0002400181,0.000001499458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002758805,"about_ca_system_score_gemma":0.0001993864,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6811988,"about_ca_topic_score_gemma":0.9769777,"domain_scores_codex":[0.9971851,0.0003056954,0.001079204,0.0004985291,0.0004984806,0.0004330524],"domain_scores_gemma":[0.9980186,0.0004373098,0.0003696348,0.0002804349,0.0006921173,0.0002018947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001868159,0.0002551522,0.1461264,0.002255628,0.002908122,0.000111235,0.0007298439,0.4792165,0.009275272,0.00005432792,0.3426748,0.01620601],"study_design_scores_gemma":[0.0008632753,0.00005646222,0.01325849,0.0002548149,0.0002433932,0.00002369755,0.0002686128,0.9735653,0.0001471365,0.00005014484,0.01086588,0.0004027683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9742852,0.0001891767,0.02300143,0.00003207328,0.0007196306,0.0004489281,0.0007575313,0.0001367077,0.0004293091],"genre_scores_gemma":[0.9940605,0.0001571993,0.004646013,0.0000915983,0.000101868,0.00001067415,0.0005793613,0.00004404561,0.0003086989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4943489,"threshold_uncertainty_score":0.9998991,"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."}}