{"id":"W2770230962","doi":"10.1002/cjs.11496","title":"Checking validity of monotone domain mean estimators","year":2019,"lang":"en","type":"preprint","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Estimator; Monotonic function; Domain (mathematical analysis); Monotone polygon; Inference; Mathematics; Population; Applied mathematics; Mathematical optimization; Measure (data warehouse); Statistics; Computer science; Artificial intelligence; Mathematical analysis; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001554656,0.0003519648,0.001224241,0.0004050118,0.00007696558,0.00009556627,0.0006485404,0.0003278881,0.0004074214],"category_scores_gemma":[0.004834949,0.0003331056,0.000187458,0.0001328096,0.0002878192,0.00005053336,0.00009273835,0.001137726,0.000007577851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003247656,"about_ca_system_score_gemma":0.003811879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001824279,"about_ca_topic_score_gemma":0.002633929,"domain_scores_codex":[0.9970499,0.0003181861,0.001443968,0.0002497965,0.0004894183,0.0004487722],"domain_scores_gemma":[0.9938383,0.002119038,0.001831781,0.0005194632,0.0009011712,0.0007902632],"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":[0.00002679575,0.00005543152,0.004791766,0.002128959,0.0002871171,0.0006521659,0.001836336,0.0001861993,0.000029796,0.9615481,0.01706395,0.01139336],"study_design_scores_gemma":[0.0002974611,0.0001525901,0.001554462,0.001074265,0.0002670517,0.00007445006,0.0001419234,0.002196818,0.0001287523,0.9932964,0.000487566,0.0003281903],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009588242,0.00009838148,0.9832525,0.00007032982,0.002446557,0.000258324,0.003540377,0.000006398792,0.0007389216],"genre_scores_gemma":[0.1193038,0.00002085576,0.8802814,0.00003077659,0.0002569319,0.000002282515,0.00001628487,0.00005311854,0.00003456519],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1097156,"threshold_uncertainty_score":0.9999121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1065073843077188,"score_gpt":0.3567251940120499,"score_spread":0.2502178097043311,"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."}}