{"id":"W2247780947","doi":"","title":"A kernel method for modelling interval censored competing risks: theory and methods","year":2009,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Interval (graph theory); Kernel (algebra); Statistics; Mathematics; Computer science; Econometrics; Applied mathematics; Combinatorics","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":[],"consensus_categories":[],"category_scores_codex":[0.01649501,0.0002850091,0.0004019805,0.0000370521,0.0004096487,0.000410681,0.0006892476,0.0002766484,0.00004417354],"category_scores_gemma":[0.0009864629,0.0001572119,0.0002119008,0.0001451553,0.00007554138,0.00004537475,0.0006783421,0.0004243805,0.000001902082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002700046,"about_ca_system_score_gemma":0.00002235822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009408617,"about_ca_topic_score_gemma":0.00047384,"domain_scores_codex":[0.9911566,0.007212713,0.0004253471,0.0006933008,0.0001779022,0.0003341422],"domain_scores_gemma":[0.9913371,0.007093625,0.0003866585,0.0002822816,0.0007519776,0.0001483488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004963201,0.0001510496,0.0003446488,0.0001017204,0.00006854175,0.000001061255,0.003377267,0.001123222,0.04551177,0.06787056,0.00009549215,0.881305],"study_design_scores_gemma":[0.0004083089,0.000003329423,0.003680549,0.001977295,0.0001457033,0.0000210085,0.0007878783,0.7811177,0.04325661,0.1503965,0.01732989,0.0008752231],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1483673,0.001929403,0.8418412,0.002922805,0.0001244543,0.0004757085,0.0001610577,0.0001139174,0.004064206],"genre_scores_gemma":[0.2460673,0.000739883,0.7519197,0.0001135475,0.00006425805,0.00003627944,0.0004136664,0.000005032575,0.0006403651],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8804298,"threshold_uncertainty_score":0.6410915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05382385579500362,"score_gpt":0.2989636952910761,"score_spread":0.2451398394960725,"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."}}