{"id":"W4413284012","doi":"10.1007/s42452-025-06817-5","title":"A systematic review of neural network applications for groundwater level prediction","year":2025,"lang":"en","type":"review","venue":"Discover Applied Sciences","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"West African Science Service Centre on Climate Change and Adapted Land Use; International Development Research Centre","keywords":"Artificial neural network; Groundwater; Computer science; Environmental science; Artificial intelligence; Geology; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.009755285,0.00144942,0.004010329,0.007778093,0.0004247309,0.002048637,0.001907859,0.001400339,0.0034762],"category_scores_gemma":[0.05349719,0.0006591508,0.007172246,0.007201045,0.0005714843,0.00169992,0.001179148,0.001077503,0.0003597445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002210224,"about_ca_system_score_gemma":0.009775702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007740206,"about_ca_topic_score_gemma":0.01965203,"domain_scores_codex":[0.9927405,0.002818078,0.002552378,0.0005562102,0.001226155,0.0001068439],"domain_scores_gemma":[0.9680592,0.02442439,0.003293737,0.0005079983,0.003559267,0.0001553017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001753873,0.00003057484,0.0009414076,0.8127238,0.007622264,0.00009934155,0.0001315695,0.001278372,0.0002461862,0.000795438,0.002894685,0.1730609],"study_design_scores_gemma":[0.0001318732,0.000358833,0.004075351,0.89051,0.04227129,0.0002951945,0.0002131005,0.001217558,0.0005386462,0.00166506,0.05865924,0.00006390351],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007174637,0.9968346,0.0009526326,0.0004414734,0.000173594,0.0001556799,0.0003804784,0.00001452084,0.0003296571],"genre_scores_gemma":[0.01121274,0.9855905,0.002014332,0.0003886244,0.00008095547,0.0003114132,0.0002714252,0.00001007964,0.0001199291],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009755285,"threshold_uncertainty_score":0.05159152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06133496577062432,"score_gpt":0.3220342197746771,"score_spread":0.2606992540040527,"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."}}