{"id":"W4380288337","doi":"","title":"Tassement de la recharge amont lors de la mise en eau de grands barrages en enrochements","year":2000,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Geotechnical and Geomechanical Engineering","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Settlement (finance); Wetting; Upstream (networking); Environmental science; Geology; Geotechnical engineering; Hydrology (agriculture); Materials science; Engineering; Computer science; Telecommunications; Composite material; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01198086,0.0006998571,0.0006372666,0.0002243292,0.0002726365,0.0003971661,0.001683154,0.001168009,0.000811378],"category_scores_gemma":[0.001878302,0.0008208499,0.0004296641,0.0004299039,0.000223661,0.000136531,0.0009350443,0.002097531,0.0001057241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001095982,"about_ca_system_score_gemma":0.0002794256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002922361,"about_ca_topic_score_gemma":0.000315881,"domain_scores_codex":[0.9900705,0.006625258,0.0008359395,0.0008546753,0.0004984123,0.001115202],"domain_scores_gemma":[0.9934794,0.003648323,0.0002070849,0.001688832,0.0003076919,0.0006687196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008772579,0.002909329,0.001650245,0.00236937,0.001061921,0.0001884332,0.03769017,0.3126672,0.2387907,0.1392828,0.004095578,0.2592064],"study_design_scores_gemma":[0.002106447,0.000003481309,0.005859138,0.005623858,0.0003138835,0.00009941643,0.0002848826,0.2507464,0.2758642,0.02053336,0.4366843,0.001880654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1469628,0.00281656,0.7870976,0.006905521,0.0003243455,0.0007606877,0.0001169544,0.0009633639,0.05405215],"genre_scores_gemma":[0.8693222,0.007486952,0.1137404,0.0001016808,0.00009543564,0.0002989101,0.0002656775,0.0001590282,0.008529717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7223594,"threshold_uncertainty_score":0.9994242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004841249244274829,"score_gpt":0.2078437996227165,"score_spread":0.2030025503784416,"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."}}