{"id":"W2332353991","doi":"","title":"RELATION BETWEEN MONITORING AND DESIGN ASPECTS OF LARGE EARTH DAMS","year":2006,"lang":"en","type":"article","venue":"","topic":"Dam Engineering and Safety","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geodetic datum; Finite element method; Deformation monitoring; Foundation (evidence); Geotechnical engineering; Deformation (meteorology); Nonlinear system; Bedrock; Engineering; Process (computing); Geology; Structural engineering; Computer science; Geodesy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001554952,0.0003725688,0.0001842186,0.00159824,0.000441522,0.00104627,0.0005351288,0.0008896484,0.001533386],"category_scores_gemma":[0.01205866,0.0003695748,0.0001749701,0.001017321,0.001005002,0.0008082496,0.0004564884,0.0003274166,0.000200032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165299,"about_ca_system_score_gemma":0.0008466362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008561819,"about_ca_topic_score_gemma":0.008648944,"domain_scores_codex":[0.9987785,0.0004273107,0.00007726371,0.0001502824,0.0004386544,0.0001279657],"domain_scores_gemma":[0.9839928,0.008564565,0.004377439,0.0006581999,0.001925428,0.0004816879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008568871,0.0003824999,0.5285847,0.0002805888,0.0000549114,0.001293613,0.001196359,0.2537174,0.03500253,0.02564721,0.001429387,0.151554],"study_design_scores_gemma":[0.00004859334,0.0009069851,0.6963956,0.0001123644,0.00007416203,0.001679564,0.001594115,0.241786,0.02970692,0.01834686,0.009249673,0.00009918517],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9192456,0.0006932839,0.06124822,0.0003928592,0.00001601051,0.0001250428,0.0002040375,0.0002996652,0.01777534],"genre_scores_gemma":[0.9956469,0.0001157582,0.003347822,0.00001194272,0.000007004912,0.00001267773,0.00004685495,0.000008872807,0.0008022605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008561819,"threshold_uncertainty_score":0.01702398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01174743155710987,"score_gpt":0.211454939941514,"score_spread":0.1997075083844042,"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."}}