{"id":"W4401783362","doi":"10.20944/preprints202408.1292.v1","title":"Quantitative Evaluations of Pumping-Induced Land Subsidence and Mitigation Strategies by Integrated Remote Sensing and Site-Specific Hydrogeological Observations","year":2024,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Hydrogeology; Subsidence; Remote sensing; Environmental science; Geology; Geomorphology; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006138717,0.0004550562,0.0002614073,0.0005911993,0.0001371148,0.0004087501,0.0002920333,0.0002891358,0.0004834238],"category_scores_gemma":[0.0005975082,0.0001512374,0.0003600943,0.0005269573,0.0002000745,0.000667469,0.0002714598,0.000155106,0.00009398731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003125127,"about_ca_system_score_gemma":0.0003970267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005758434,"about_ca_topic_score_gemma":0.008268086,"domain_scores_codex":[0.9998491,0.00002832116,0.00001066011,0.00004170933,0.00004110876,0.00002915773],"domain_scores_gemma":[0.9997999,0.00004947248,0.00004230698,0.00003073161,0.00006102439,0.00001659398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004257655,0.0004348647,0.2992316,0.0003087774,0.0003397865,0.0003498744,0.0003390784,0.4302545,0.09393274,0.001093358,0.0008426894,0.172447],"study_design_scores_gemma":[0.0000238367,0.0002961324,0.206111,0.0000187151,0.0001120112,0.00004298436,0.0002539145,0.7838184,0.008320821,0.0003358134,0.0006308936,0.00003552257],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823449,0.00009525425,0.01558629,0.00003277164,0.00001052684,0.0000477138,0.0005592774,0.0002522717,0.001070936],"genre_scores_gemma":[0.9950145,0.00004257208,0.004542307,0.00000535941,0.000002249421,0.00001454443,0.0002688402,0.000006634184,0.0001030032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005758434,"threshold_uncertainty_score":0.01144981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.132965266829343,"score_gpt":0.3482703335411443,"score_spread":0.2153050667118014,"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."}}