{"id":"W4283789493","doi":"10.1002/cjs.11708","title":"Pseudo empirical likelihood inference for nonprobability survey samples","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Waterloo; Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Nonprobability sampling; Estimator; Inference; Survey sampling; Point estimation; Statistical inference; Statistics; Sampling (signal processing); Computer science; Survey data collection; Range (aeronautics); Econometrics; Survey research; Mathematics; Artificial intelligence; Engineering; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03794508,0.0008109709,0.001570178,0.002323433,0.0006783282,0.002465022,0.003396199,0.00152391,0.004964972],"category_scores_gemma":[0.2402834,0.000861693,0.001285381,0.002459054,0.004516856,0.004818644,0.002804239,0.003301588,0.0005975053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001678872,"about_ca_system_score_gemma":0.002331288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003792506,"about_ca_topic_score_gemma":0.00285738,"domain_scores_codex":[0.9602979,0.03304542,0.0008788826,0.001972367,0.003503031,0.0003024705],"domain_scores_gemma":[0.7705116,0.2087788,0.005434881,0.009608541,0.005018194,0.0006479502],"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":[0.0001055558,0.00006761364,0.003976581,0.0003002829,0.0001552388,0.0001728089,0.0003200153,0.05677347,0.0002596171,0.8790061,0.001575218,0.05728749],"study_design_scores_gemma":[0.00006364433,0.0000491657,0.001657959,0.0001094467,0.00002855921,0.0001060822,0.00008259108,0.4136817,0.0003960993,0.58103,0.00276969,0.00002504019],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004245806,0.0002071149,0.9943911,0.0002684771,0.0000274526,0.00006765809,0.0000652682,0.0000536968,0.0006733087],"genre_scores_gemma":[0.4026015,0.001243124,0.5899196,0.000711911,0.0002547775,0.001175282,0.0007206586,0.0001338522,0.003239352],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03794508,"threshold_uncertainty_score":0.2006751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1647527977897741,"score_gpt":0.3922188911423007,"score_spread":0.2274660933525266,"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."}}