{"id":"W4290613457","doi":"10.1177/00491241221113877","title":"The Design and Optimality of Survey Counts: A Unified Framework Via the Fisher Information Maximizer","year":2022,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Hong Kong Polytechnic University","keywords":"Fisher information; Range (aeronautics); Mathematics; Statistics; Generalized linear model; Computer science; Econometrics; Optimal design; Mathematical optimization","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06739856,0.00006217152,0.0001433408,0.00003304351,0.0007821962,0.00004634321,0.0003266259,0.0001059243,0.0002607098],"category_scores_gemma":[0.01993017,0.00003191103,0.00003682996,0.0002755684,0.0005038368,0.00004312336,0.0002632465,0.0007828961,0.00000515025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004422359,"about_ca_system_score_gemma":0.00004637995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009350671,"about_ca_topic_score_gemma":4.065705e-7,"domain_scores_codex":[0.9831102,0.01592623,0.0002667401,0.0001018386,0.0003909144,0.0002040904],"domain_scores_gemma":[0.9493376,0.04999187,0.0000915975,0.0002873913,0.0002642646,0.00002729928],"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":[0.001029419,0.000255829,0.005992867,0.0001444608,0.0002036965,0.00000151873,0.007119836,0.0002288273,0.0002001848,0.4408302,0.07579109,0.468202],"study_design_scores_gemma":[0.00005499393,0.0001048469,0.007884416,0.000004116904,0.000003587587,0.000001393333,0.0005302235,0.002535113,0.00009247405,0.9843289,0.004409548,0.00005034882],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00526478,0.0001432109,0.9920392,0.0008009196,0.00006133912,0.0004193135,0.00001358866,0.00005664245,0.00120101],"genre_scores_gemma":[0.1036737,0.0001001751,0.8957006,0.0001126765,0.0000189005,0.0002364732,0.000008276874,0.000007682564,0.000141583],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5434987,"threshold_uncertainty_score":0.9883254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6171696352915063,"score_gpt":0.5685923866874328,"score_spread":0.04857724860407342,"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."}}