{"id":"W6998654320","doi":"","title":"Application de la méthode MASW pour la détection de zones de faiblesse sous les chaussées","year":2002,"lang":"fr","type":"other","venue":"Knowledge UdeS (Institutional Deposit of the University of Sherbrooke)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Marl; Geophysical prospecting; Homogeneous","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":[0.0006059963,0.000782032,0.0005502473,0.001328243,0.0004615251,0.001439212,0.0006355591,0.0009446371,0.00338647],"category_scores_gemma":[0.001611531,0.0004778662,0.00074928,0.0007669433,0.0005491494,0.00074492,0.0006442238,0.0008611295,0.001034654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003948981,"about_ca_system_score_gemma":0.001234445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00405873,"about_ca_topic_score_gemma":0.005948607,"domain_scores_codex":[0.9995263,0.00004982438,0.00002124249,0.0001131676,0.0002547166,0.00003481362],"domain_scores_gemma":[0.9992761,0.000329855,0.00005991691,0.00007748406,0.0002358347,0.00002073687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000184394,0.0000815982,0.008101376,0.0005212912,0.00008924112,0.0002100813,0.0005946595,0.06933002,0.4094717,0.009920403,0.001680065,0.4998151],"study_design_scores_gemma":[0.00002756216,0.000151794,0.01027432,0.00005670342,0.00004842271,0.0004793806,0.0004818361,0.7002781,0.2616168,0.00449716,0.02199129,0.00009663983],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05865981,0.000261646,0.9365149,0.0001291492,0.00007079891,0.00008865838,0.0002023649,0.001799281,0.002273445],"genre_scores_gemma":[0.2181135,0.0003538676,0.7756802,0.00003904495,0.0000195544,0.000158137,0.0002399424,0.0002798388,0.00511594],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00405873,"threshold_uncertainty_score":0.01132888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01396325444066807,"score_gpt":0.2193261776165711,"score_spread":0.2053629231759031,"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."}}