{"id":"W4387878723","doi":"10.1680/jenes.23.00051","title":"Groundwater resource exploration and mapping methods: a review","year":2023,"lang":"en","type":"review","venue":"Journal of Environmental Engineering and Science","topic":"Groundwater and Watershed Analysis","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Interpretability; Computer science; Strengths and weaknesses; Resource (disambiguation); Groundwater; Risk analysis (engineering); Context (archaeology); Environmental resource management; Data science; Environmental science; Remote sensing; Business; Engineering; Geography; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002202863,0.001203089,0.001688886,0.00435739,0.000512514,0.00198662,0.001653212,0.001463762,0.004234405],"category_scores_gemma":[0.004793119,0.0005888866,0.001344924,0.007377675,0.000728244,0.002416543,0.0009218718,0.001471045,0.001726473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008628166,"about_ca_system_score_gemma":0.00331956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003891088,"about_ca_topic_score_gemma":0.00432683,"domain_scores_codex":[0.9990356,0.0002222699,0.0001694404,0.0001610255,0.0003636121,0.00004806626],"domain_scores_gemma":[0.9963576,0.002537848,0.0002500849,0.00008769041,0.0006995477,0.0000671501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003528149,0.00006302052,0.0004307312,0.0533906,0.0001676109,0.0001212745,0.0001625025,0.0009216543,0.0009484322,0.004722171,0.01630446,0.9227322],"study_design_scores_gemma":[0.00001058145,0.0001137534,0.001711266,0.02304569,0.000517645,0.0009200652,0.0002133811,0.0006711489,0.000936199,0.004684275,0.9671106,0.00006551014],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001872812,0.9970742,0.001121546,0.0003066311,0.0001695618,0.00001455315,0.00004821457,0.00001539686,0.001062623],"genre_scores_gemma":[0.001021694,0.9970873,0.001379684,0.0001045008,0.0001040809,0.00001618576,0.00004599073,0.000004888509,0.0002357521],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00435739,"threshold_uncertainty_score":0.01416546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04248238280784692,"score_gpt":0.2916923993773452,"score_spread":0.2492100165694983,"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."}}