{"id":"W2900988085","doi":"10.1080/03610918.2018.1516290","title":"Calibration using power transformation","year":2018,"lang":"en","type":"article","venue":"Communications in Statistics - Simulation and Computation","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Texas A and M University","keywords":"Estimator; Statistics; Calibration; Mathematics; Nonparametric statistics; Population; Computer science; Econometrics; Demography; Sociology","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":[0.0006149602,0.000119217,0.0001456197,0.000252343,0.0003116902,0.0000898656,0.0001399914,0.00008426261,0.00002644125],"category_scores_gemma":[0.0004266588,0.0001340792,0.00001676103,0.0003449576,0.0001699047,0.0003500412,0.00004944437,0.0001195706,0.000004344783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007518462,"about_ca_system_score_gemma":0.00003873117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005730986,"about_ca_topic_score_gemma":0.000101528,"domain_scores_codex":[0.9987768,0.0002440009,0.0005363276,0.0001545493,0.0001647572,0.0001235954],"domain_scores_gemma":[0.9979355,0.001170686,0.0001862032,0.0003522932,0.0003150335,0.00004032697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009694603,0.0004129324,0.004932095,0.0001260013,0.00003806454,8.175321e-7,0.01620255,0.08337823,0.0003256425,0.7971498,0.0005315213,0.09680542],"study_design_scores_gemma":[0.0002539337,0.0000400159,0.002456028,0.00003755574,0.00001098334,0.000001990023,0.0001692901,0.7877175,0.00005574338,0.2089953,0.0001474409,0.0001141758],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07919805,0.000027454,0.9194093,0.0001105585,0.00006502215,0.0002864352,0.0000405099,0.0001469827,0.0007156739],"genre_scores_gemma":[0.6584554,0.00001101416,0.3413017,0.00004359295,0.00001336839,0.000009899938,0.0001460843,0.00001221806,0.000006693218],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7043393,"threshold_uncertainty_score":0.5467591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3697412499577581,"score_gpt":0.5172665598279156,"score_spread":0.1475253098701575,"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."}}