{"id":"W2901132294","doi":"10.1002/cjs.11466","title":"Rank‐based inference with responses missing not at random","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Missing data; Estimator; Outlier; Statistics; Robustness (evolution); Statistical inference; Computer science; Inference; Robust regression; Monte Carlo method; Robust statistics; Regression analysis; Mathematics; Econometrics; Data mining; Artificial intelligence","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000825847,0.000171573,0.000397699,0.0002104143,0.0002803333,0.00009628426,0.0002253222,0.00006749719,0.001201031],"category_scores_gemma":[0.01371123,0.0001297305,0.00003867446,0.0001681166,0.0005645718,0.00005888676,0.000009954401,0.0002317633,0.00001964939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001722766,"about_ca_system_score_gemma":0.00224546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005051861,"about_ca_topic_score_gemma":0.008496227,"domain_scores_codex":[0.9984015,0.0002480491,0.0005356024,0.0001325233,0.0003089127,0.0003734222],"domain_scores_gemma":[0.9920549,0.005635374,0.000385928,0.0002139316,0.000935702,0.0007741587],"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":[0.00846262,0.0001420797,0.02160688,0.0005529757,0.0004048315,0.004932687,0.004103458,0.00003931525,0.002588581,0.713964,0.08529977,0.1579028],"study_design_scores_gemma":[0.01401365,0.005597305,0.03041442,0.002232997,0.0008492864,0.001081544,0.0003941666,0.01242665,0.01395366,0.8820075,0.03540153,0.00162726],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02811592,0.00003653927,0.9692792,0.000473544,0.0002607457,0.0000974209,0.0005368069,0.000007261043,0.001192581],"genre_scores_gemma":[0.4189819,0.000002606592,0.5803539,0.0003313367,0.0001160775,9.594227e-7,0.000001616869,0.00001912475,0.000192501],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.390866,"threshold_uncertainty_score":0.999712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1321928907379329,"score_gpt":0.3601690560726994,"score_spread":0.2279761653347665,"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."}}