{"id":"W7097221113","doi":"","title":"La revue canadienne de statistique Kendall’s tau for Serial Dependence","year":2008,"lang":"en","type":"article","venue":"","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Statistical analysis; Sequence (biology); Bayesian probability; Field (mathematics)","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":[0.06075838,0.003390961,0.007935384,0.01021975,0.002758813,0.01207049,0.007143696,0.009243662,0.005660399],"category_scores_gemma":[0.1780722,0.003776246,0.005632821,0.01404329,0.01912034,0.01988932,0.006205484,0.03202908,0.003460429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006959547,"about_ca_system_score_gemma":0.009365631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009952212,"about_ca_topic_score_gemma":0.005454681,"domain_scores_codex":[0.9485759,0.03310252,0.003521451,0.005549989,0.008129425,0.001120697],"domain_scores_gemma":[0.6762568,0.2922525,0.004465253,0.01670732,0.009153679,0.001164496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004684101,0.00003172712,0.000690675,0.0005987409,0.0003123281,0.0001273801,0.0003983977,0.005235399,0.00021558,0.9355834,0.007862836,0.04889676],"study_design_scores_gemma":[0.00001689591,0.00001658834,0.0004477847,0.0002196569,0.00008066319,0.000158635,0.00003610334,0.01887012,0.0001654435,0.9558578,0.02407777,0.00005258854],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001788653,0.06019641,0.9180567,0.01168766,0.003478913,0.00003922592,0.0002916275,0.0003117334,0.004149107],"genre_scores_gemma":[0.1189419,0.09759194,0.7245085,0.009413254,0.03061539,0.0009983723,0.0009361504,0.002418241,0.0145763],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06075838,"threshold_uncertainty_score":0.3213249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07084194821187996,"score_gpt":0.3527555040765771,"score_spread":0.2819135558646972,"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."}}