{"id":"W4312164519","doi":"10.1002/cjs.11753","title":"Unweighted estimation based on optimal sample under measurement constraints","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Estimator; Mathematical optimization; Mathematics; Measure (data warehouse); Computer science; Efficiency; Sampling (signal processing); Martingale (probability theory); Statistics; Algorithm; Data mining","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001043785,0.0001374055,0.0002614296,0.0002202134,0.0003273601,0.00003399401,0.000168013,0.00003056584,0.001459996],"category_scores_gemma":[0.003409689,0.0001350901,0.00004980142,0.0001332234,0.0001350948,0.00004394731,0.000009638148,0.000364252,0.00000220019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000732063,"about_ca_system_score_gemma":0.001740967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000190876,"about_ca_topic_score_gemma":0.0006289346,"domain_scores_codex":[0.9982209,0.0002198964,0.0004947265,0.0001246982,0.0006440469,0.0002957433],"domain_scores_gemma":[0.9971734,0.001429563,0.0003208659,0.0001521608,0.0004121768,0.0005117798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006186368,0.00007935784,0.00002653753,0.00004036033,0.00005248073,0.0003291076,0.0002111897,0.1370991,0.00002471859,0.8103659,0.01185753,0.03985193],"study_design_scores_gemma":[0.0008735197,0.000590805,0.0001275985,0.00005225951,0.00009198678,0.00007089025,0.0003011093,0.1852621,0.00004571881,0.8096499,0.002726873,0.0002072035],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003430429,0.00002036828,0.9956648,0.0003069954,0.0003415632,0.0001340143,0.002833222,0.000006583508,0.0003494251],"genre_scores_gemma":[0.2948933,6.913245e-7,0.7047062,0.0003152585,0.00002742549,0.000004788326,0.00001722288,0.00001984064,0.00001532204],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2945502,"threshold_uncertainty_score":0.9994528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1649113030814011,"score_gpt":0.3607964750029343,"score_spread":0.1958851719215332,"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."}}