{"id":"W2963246254","doi":"","title":"Optimum Statistical Estimation with Strategic Data Sources","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Estimator; Polynomial regression; Computer science; Regression; Regression analysis; Kernel (algebra); Linear regression; Range (aeronautics); Proper linear model; Mathematical optimization; Econometrics; Statistics; Mathematics; Machine learning; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002375707,0.0001031898,0.0001705248,0.0001379741,0.00008311386,0.0004868607,0.00131793,0.00003723351,0.0009093566],"category_scores_gemma":[0.002411424,0.00005692643,0.000008376201,0.0005576206,0.000230168,0.0009678762,0.0003861863,0.0001400285,0.00138043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003186176,"about_ca_system_score_gemma":0.0003618951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004088895,"about_ca_topic_score_gemma":0.00007351554,"domain_scores_codex":[0.9962413,0.0001303891,0.000302321,0.0005509907,0.002495439,0.0002795562],"domain_scores_gemma":[0.9969198,0.001093197,0.00007411904,0.001175376,0.0004347067,0.0003027643],"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":[0.0008267559,0.0005047561,0.006106871,0.0000144385,0.00008397733,0.0004350631,0.0009682518,0.3178747,0.00004240241,0.04233829,0.120052,0.5107525],"study_design_scores_gemma":[0.0004490832,0.000207464,0.0006703534,0.000002848732,0.000003741222,0.00002373035,0.002036104,0.879962,0.00004915238,0.1140192,0.002461429,0.0001148181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007214133,0.00003067608,0.9822283,0.0005493456,0.00006032647,0.000137117,0.0000749496,0.00005673674,0.009648376],"genre_scores_gemma":[0.5151808,0.000001564316,0.4806665,0.00004717947,0.000072488,0.000005994982,0.0001082611,0.00001235977,0.003904827],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5620874,"threshold_uncertainty_score":0.9993971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5456077650671064,"score_gpt":0.5258773785639367,"score_spread":0.01973038650316972,"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."}}