{"id":"W2618479281","doi":"","title":"An Approximate Design Effect for Unequal Weighting When Measurements May Correlate with Selection Probabilities","year":2000,"lang":"en","type":"article","venue":"Survey methodology","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Weighting; Statistics; Mathematics; Computer science; Artificial intelligence; Physics","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","metaepi_narrow","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.1411556,0.0004257499,0.001034203,0.0003052128,0.0003886597,0.0002275762,0.0008078509,0.0002856157,0.0009832893],"category_scores_gemma":[0.01224405,0.0002939175,0.0001372736,0.0007900334,0.0003064001,0.0005859789,0.00004463154,0.0002772199,0.00008585351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001367479,"about_ca_system_score_gemma":0.0001518569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004897322,"about_ca_topic_score_gemma":0.00015359,"domain_scores_codex":[0.9249417,0.07100408,0.0009532811,0.001282311,0.001045394,0.000773208],"domain_scores_gemma":[0.9584668,0.03970522,0.0003578095,0.0006851662,0.0005804582,0.0002045364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.04114296,0.0006727774,0.1027924,0.0001016969,0.0004922327,0.00001007151,0.009266234,0.06138249,0.2164698,0.001054291,0.001193588,0.5654215],"study_design_scores_gemma":[0.008704267,0.0297036,0.07245251,0.00009944568,0.0002845109,0.0001874378,0.001189755,0.1512279,0.6366047,0.09508958,0.001821526,0.002634716],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2503586,0.0000780136,0.7465387,0.00002427819,0.0003769712,0.001554311,0.00002113939,0.0001291338,0.0009188364],"genre_scores_gemma":[0.1621968,0.00000154553,0.8358517,0.00007189196,0.00007144724,0.0003505485,0.00002260347,0.0000510908,0.001382394],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5627868,"threshold_uncertainty_score":0.9999513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6404714675082755,"score_gpt":0.5156032129815941,"score_spread":0.1248682545266815,"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."}}