{"id":"W3047295947","doi":"10.1002/cjs.11566","title":"Empirical and conditional likelihoods for two‐phase studies","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Covariate; Estimator; Statistics; Mathematics; Econometrics; Parametric statistics; Regression analysis; Empirical likelihood","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[],"category_scores_codex":[0.0002881835,0.00010185,0.0003203129,0.00005777532,0.0001088978,0.0000388074,0.00008673032,0.00003261672,0.0001244028],"category_scores_gemma":[0.01237815,0.00008657859,0.00003406568,0.00006609465,0.000201365,0.00004000787,0.00000874429,0.0001521585,0.000001962605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004249641,"about_ca_system_score_gemma":0.000576746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002243712,"about_ca_topic_score_gemma":0.0002929649,"domain_scores_codex":[0.9991137,0.00005908,0.0004142096,0.00009449387,0.000125547,0.0001929069],"domain_scores_gemma":[0.9957483,0.002726653,0.0001783858,0.00004715725,0.0005261044,0.000773387],"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":[0.00005452945,0.00002525084,0.000669807,0.0002192065,0.0001619191,0.0002240741,0.001730457,0.000003368584,0.0000413792,0.7420363,0.2346534,0.02018027],"study_design_scores_gemma":[0.001663096,0.0009376519,0.0003953797,0.00004774301,0.0001450281,0.00007853049,0.0005661353,0.002044641,0.00005194628,0.9824433,0.0114866,0.0001399433],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006128779,0.0003896379,0.9877046,0.002598755,0.0001723968,0.0001071122,0.002811098,0.000003650295,0.00008395685],"genre_scores_gemma":[0.1447468,0.00002258924,0.8533673,0.001519009,0.0002997846,0.000003301553,0.000008569548,0.0000153137,0.00001735705],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.240407,"threshold_uncertainty_score":0.995941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3189474729350864,"score_gpt":0.4673435364813731,"score_spread":0.1483960635462867,"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."}}