{"id":"W2589994821","doi":"10.71781/15329","title":"Diagnostics robustes à des délais individuels en utilisant les estimateurs robustes RA-ARX","year":2004,"lang":"fr","type":"dissertation","venue":"Open MIND","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Psychology; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002849022,0.0008534526,0.001074139,0.0004465808,0.001521791,0.003024401,0.004736793,0.0009343493,0.00982336],"category_scores_gemma":[0.007337997,0.0007540549,0.0003478038,0.001341836,0.0008165446,0.0009017593,0.0009144664,0.0008154803,0.002451025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003232344,"about_ca_system_score_gemma":0.00104369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003015782,"about_ca_topic_score_gemma":0.004335615,"domain_scores_codex":[0.9940554,0.0003197611,0.001736959,0.0016516,0.001263152,0.000973123],"domain_scores_gemma":[0.9913864,0.004827803,0.001190772,0.001287274,0.0008800444,0.0004277589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005571094,0.0006228867,0.01010503,0.0001088436,0.0001075532,0.00006508291,0.009465675,0.01760514,0.0002131235,0.003304395,0.003485331,0.9548612],"study_design_scores_gemma":[0.004204547,0.002475041,0.1138262,0.01989034,0.003217162,0.0005142459,0.0776483,0.07014322,0.1119081,0.1955607,0.3915571,0.009055124],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9190898,0.005343932,0.02517185,0.001677007,0.001141307,0.00438328,0.001617826,0.00005790941,0.04151708],"genre_scores_gemma":[0.3950047,0.001863329,0.578854,0.00005036587,0.000223739,0.0005311046,0.001547228,0.0001454095,0.02178017],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9458061,"threshold_uncertainty_score":0.9997781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2416203457435183,"score_gpt":0.4457483122096931,"score_spread":0.2041279664661748,"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."}}