{"id":"W2272779360","doi":"10.5539/ijsp.v5n2p1","title":"On Consistency of Absolute Deviations Estimators of Convex Functions","year":2016,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Least absolute deviations; Mathematics; Estimator; Rate function; Consistency (knowledge bases); Function (biology); Applied mathematics; Convex function; Convex set; Standard deviation; Convex combination; Queue; Subderivative; Regular polygon; Mathematical optimization; Large deviations theory; Combinatorics; Statistics; Convex optimization; Discrete mathematics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0006372218,0.00007935987,0.0002686578,0.00007151474,0.00003878271,0.00001593081,0.0001314385,0.00003635744,0.0002393063],"category_scores_gemma":[0.00948864,0.000050493,0.00005366865,0.00004628875,0.00028172,0.00005036027,0.0000297446,0.00007820936,0.000001413948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003659774,"about_ca_system_score_gemma":0.00012362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001328702,"about_ca_topic_score_gemma":0.000007866834,"domain_scores_codex":[0.9986169,0.00008611506,0.0007809502,0.00008941822,0.0003536092,0.00007300212],"domain_scores_gemma":[0.9928491,0.004867288,0.000658107,0.0001076805,0.001450661,0.00006715584],"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":[0.0001023728,0.000198893,0.004147757,0.00006363076,0.0001125002,0.000003300557,0.00006316622,0.000003308252,0.000438131,0.9671665,0.0008708538,0.02682958],"study_design_scores_gemma":[0.0004651257,0.0003207733,0.02494919,0.0001968596,0.00004873606,0.00001797909,0.00001711366,0.0001954622,0.0003613773,0.9732317,0.0001399179,0.00005576455],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1408333,0.00002202349,0.856553,0.0003537394,0.000345029,0.00007743987,0.001039395,0.000003021044,0.0007730702],"genre_scores_gemma":[0.6908234,0.00002877943,0.3090645,0.00001614664,0.00002232676,0.000001481214,0.000001130255,0.000004232292,0.00003801547],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5499901,"threshold_uncertainty_score":0.9988549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06405000575808079,"score_gpt":0.3647082774149025,"score_spread":0.3006582716568217,"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."}}