{"id":"W4400243311","doi":"10.11159/ijci.2024.006","title":"Stability Analysis of Surface and Subsurface Geological Hazards Using Numerical Approach in Hydropower Project of India- a Case Study","year":2024,"lang":"en","type":"article","venue":"International Journal of Civil Infrastructure","topic":"Dam Engineering and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydropower; Geologic hazards; Geology; Stability (learning theory); Subsurface flow; Environmental science; Geotechnical engineering; Mining engineering; Civil engineering; Landslide; Engineering; Computer science; Groundwater","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":[0.0002667987,0.0002817588,0.0002247388,0.001236655,0.0005077849,0.000680701,0.0004105181,0.0005133036,0.0007769991],"category_scores_gemma":[0.0006566676,0.0001988319,0.0004547169,0.000759495,0.0005343716,0.0002431579,0.0004999328,0.0002156733,0.00008160107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007755898,"about_ca_system_score_gemma":0.0004679746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0154119,"about_ca_topic_score_gemma":0.01324893,"domain_scores_codex":[0.9998554,0.00003838995,0.000009902976,0.0000211052,0.00004547751,0.00002969169],"domain_scores_gemma":[0.9995887,0.0002068868,0.00007091456,0.00002229452,0.00008200455,0.00002921785],"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":[0.0001253943,0.000101513,0.06627821,0.0001993607,0.00004474028,0.002793052,0.0008485596,0.886939,0.01111237,0.005894667,0.0006463595,0.02501669],"study_design_scores_gemma":[0.000004501564,0.0001065376,0.02449148,0.00001845776,0.00002131127,0.0004312847,0.001159042,0.968846,0.002648567,0.001439251,0.0008101327,0.00002344582],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.975496,0.0001777258,0.01937168,0.0001090014,0.000006796442,0.00003527009,0.0001087605,0.00008257848,0.004612225],"genre_scores_gemma":[0.9961009,0.00008704466,0.003046747,0.000003256705,0.000001952215,0.00001037158,0.00004107388,0.000005969352,0.0007027127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0154119,"threshold_uncertainty_score":0.03064442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01407407418470047,"score_gpt":0.2836018220092823,"score_spread":0.2695277478245818,"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."}}