{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006163221,0.0001192204,0.0002258686,0.00003094046,0.000111323,0.00001899375,0.0001560767,0.0001011208,0.000524398],"category_scores_gemma":[0.004157399,0.0001058377,0.00004035377,0.00006657645,0.00008472316,0.00004945064,0.00002515649,0.000120476,0.000007326709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008638349,"about_ca_system_score_gemma":0.0001926101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001854914,"about_ca_topic_score_gemma":0.01066061,"domain_scores_codex":[0.9989467,0.0001276884,0.0002334081,0.0002125689,0.00006004498,0.0004196097],"domain_scores_gemma":[0.9963782,0.003067973,0.00006080019,0.0001933367,0.00009066425,0.0002089623],"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":[0.00003339369,0.00003584688,0.0004697376,0.0001128522,0.00001187875,0.00009086655,0.0007701099,5.348087e-7,0.0003425905,0.9824087,0.006654359,0.009069146],"study_design_scores_gemma":[0.0003520022,0.0001087333,0.003410083,0.00003386332,0.00001870268,0.0002019452,0.0001139307,0.001308954,0.00108904,0.991347,0.001825651,0.0001901369],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.032474,0.000003896799,0.9624302,0.0002038908,0.0001167894,0.0002286798,0.0001735741,0.00006109133,0.004307839],"genre_scores_gemma":[0.1509129,0.000009349355,0.8476848,0.0001048896,0.000105306,0.00006188675,0.000003881867,0.00001821072,0.001098804],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1184389,"threshold_uncertainty_score":0.5948871,"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."}}