{"id":"W2272293496","doi":"","title":"Groundwater Quality in Canada: A National Overview","year":2007,"lang":"en","type":"article","venue":"Tunnelling and Underground Space Technology","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Water quality; Environmental planning; Aquifer; Groundwater; Water resources; Business; Government (linguistics); Geological survey; Population; Water supply; Natural resource; Water resource management; Environmental resource management; Environmental science; Engineering; Environmental health; Environmental engineering; Political science; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0006689024,0.0001416905,0.0001983424,0.0001192519,0.0001385155,0.00002030935,0.0001312831,0.00009265497,0.0001087592],"category_scores_gemma":[0.00003318353,0.0001306149,0.00001899975,0.0004012016,0.0001647471,0.0001181578,0.0001440685,0.0001835861,0.00003292595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009273498,"about_ca_system_score_gemma":0.00006383483,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6304078,"about_ca_topic_score_gemma":0.9708389,"domain_scores_codex":[0.9987038,0.00002781541,0.0002827245,0.0003170088,0.0002959816,0.0003726169],"domain_scores_gemma":[0.9996265,0.0001132319,0.00006640395,0.0001250867,0.00001842774,0.00005030808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000358134,0.0001245558,0.8794098,0.00003319795,0.00003520933,0.00006204,0.0004878657,0.0002005197,0.002111942,0.07548103,0.0007015897,0.04131644],"study_design_scores_gemma":[0.001138961,0.00008272164,0.8848326,0.0000391575,0.00001364311,0.00006839274,0.005357438,0.0004463998,0.001056934,0.04568489,0.06064564,0.0006332324],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9743459,0.0005163842,0.01857386,0.003370588,0.00009735704,0.00009832934,0.000001085142,0.00005837896,0.002938109],"genre_scores_gemma":[0.9970118,0.0001271928,0.0005173169,0.0003621336,0.00001594152,0.00000898416,0.000002232888,0.000008540425,0.001945844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3404311,"threshold_uncertainty_score":0.5326323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02415484463536232,"score_gpt":0.2613919140256208,"score_spread":0.2372370693902585,"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."}}