{"id":"W2471145407","doi":"10.1002/sim.7011","title":"Statistical issues related to dietary intake as the response variable in intervention trials","year":2016,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Cancer Institute; National Heart, Lung, and Blood Institute; Medical Research Council; National Institutes of Health","keywords":"Reliability (semiconductor); Biomarker; Context (archaeology); Calibration; Observational error; Statistics; Computer science; Intervention (counseling); Clinical trial; Medicine; Mathematics; Internal medicine; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005412926,0.0001556342,0.0006709428,0.0001952939,0.00005271696,0.000006052644,0.00009841051,0.00007332298,0.002414582],"category_scores_gemma":[0.02907309,0.00007830095,0.00003142609,0.0004080545,0.0002483613,0.00002909914,0.0000676703,0.0002229659,0.0001188266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000178251,"about_ca_system_score_gemma":0.00005666451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008890902,"about_ca_topic_score_gemma":0.0002229305,"domain_scores_codex":[0.9973404,0.0006648891,0.0009989175,0.0002751483,0.0004370323,0.0002835767],"domain_scores_gemma":[0.9936175,0.005782272,0.0001045356,0.0002345203,0.0001327362,0.0001283994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.03475961,0.001066508,0.02282152,0.0003216074,0.0002991054,0.001584879,0.002504965,0.000008285837,0.007847004,0.3517089,0.4906373,0.08644027],"study_design_scores_gemma":[0.0163959,0.00548878,0.4906349,0.004107934,0.000198151,0.00007455846,0.002197946,0.00008008661,0.00009414973,0.3567813,0.1236779,0.0002684074],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3827965,0.008653616,0.1220153,0.4610493,0.003786844,0.00623983,0.003085733,0.0001854102,0.01218749],"genre_scores_gemma":[0.9379609,0.002242999,0.04371308,0.004848551,0.0005556899,0.000266077,0.0003028979,0.00005958709,0.01005025],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5551644,"threshold_uncertainty_score":0.9984974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05277491442254351,"score_gpt":0.4183318600881368,"score_spread":0.3655569456655933,"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."}}