{"id":"W2043174953","doi":"10.1002/cjs.11128","title":"Sequential design for nonparametric inference","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematics; Nonparametric statistics; Quantile; Statistics; Inference; Econometrics; Computer science; 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"],"consensus_categories":[],"category_scores_codex":[0.005281259,0.0001182689,0.0002938301,0.0007350514,0.0001472229,0.0002495518,0.0005904948,0.00006897961,0.0005712745],"category_scores_gemma":[0.0202373,0.00009597889,0.0000818325,0.0006316202,0.0001466233,0.0003394805,0.00001385582,0.000159278,0.0000710438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002047155,"about_ca_system_score_gemma":0.001526984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003509263,"about_ca_topic_score_gemma":0.0002874724,"domain_scores_codex":[0.997728,0.0003332291,0.0007444955,0.0001163031,0.0006048994,0.0004731017],"domain_scores_gemma":[0.9922099,0.005022662,0.0004757548,0.000196,0.0008891001,0.001206608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002872605,0.0001496962,0.03477705,0.00002567396,0.0001758282,0.0002432146,0.004673825,0.006029734,0.005693639,0.1628007,0.2772477,0.5078956],"study_design_scores_gemma":[0.004653025,0.004885816,0.04646235,0.0001387252,0.0004231604,0.001282114,0.00405526,0.03679437,0.04549244,0.4949397,0.35878,0.002092994],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003163537,0.0005920866,0.993546,0.00006235119,0.001716337,0.0001560688,0.0002354435,0.000002138479,0.0005260185],"genre_scores_gemma":[0.4166142,0.000003666963,0.5828751,0.0001029401,0.000176923,0.000001962596,0.000001074297,0.000009405007,0.000214729],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5058026,"threshold_uncertainty_score":0.9880157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3601301529286638,"score_gpt":0.4679454129079356,"score_spread":0.1078152599792718,"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."}}