{"id":"W2182062836","doi":"","title":"Managing Response Burden by Controlling Sample Selection and Survey Coverage","year":2011,"lang":"en","type":"article","venue":"","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Payroll; Sample (material); Earnings; Control (management); Survey data collection; Selection (genetic algorithm); Survey sampling; Survey methodology; Demographic economics; Business; Operations management; Economics; Statistics; Computer science; Accounting; Demography; Population; Mathematics; Sociology; Management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008958429,0.00006524406,0.00009775887,0.00004245196,0.00008781007,0.00002080585,0.00002519713,0.00003611399,0.0002549873],"category_scores_gemma":[0.0006163497,0.0000598804,0.00001390903,0.00007010796,0.000007360453,0.00009197168,0.00001062991,0.00004289831,0.000005679827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000019995,"about_ca_system_score_gemma":0.000006670949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002197108,"about_ca_topic_score_gemma":0.0003586363,"domain_scores_codex":[0.9994491,0.0001128679,0.0001577202,0.0001065684,0.00007748114,0.00009620108],"domain_scores_gemma":[0.9989761,0.0008031553,0.00006402574,0.0000727651,0.00005063108,0.00003337975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.008105922,0.0003471446,0.694385,0.0002704302,0.000275424,0.000006198269,0.01195947,0.0006402287,0.01289451,0.1872279,0.02696493,0.05692284],"study_design_scores_gemma":[0.002452814,0.000190455,0.3554651,0.00004096905,0.00006647377,0.00001700399,0.0001259187,0.25306,0.002094726,0.3831446,0.002825432,0.0005165813],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6806508,0.00001636947,0.3181645,0.00006222531,0.00003188856,0.0001137761,0.0000160389,0.00006599055,0.0008783432],"genre_scores_gemma":[0.9882624,0.000009463735,0.01102407,0.00003816721,0.00001626032,0.000003366403,0.00002183983,0.00001070292,0.000613783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3389199,"threshold_uncertainty_score":0.3321385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08036515863848734,"score_gpt":0.3113466794804006,"score_spread":0.2309815208419133,"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."}}