{"id":"W2510935139","doi":"10.6000/1929-6029.2016.05.03.8","title":"Measuring Modified Mass Energy Equivalence in Nutritional Epidemiology: A Proposal to Adapt the Biophysical Modelling Approach","year":2016,"lang":"en","type":"article","venue":"International Journal of Statistics in Medical Research","topic":"Diet and metabolism studies","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dieting; Confounding; Population; Energy (signal processing); Environmental health; Sample (material); Medicine; Epidemiology; Gerontology; Psychology; Obesity; Mathematics; Weight loss; Statistics; Endocrinology; Pathology; Physics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00736388,0.0001089126,0.0004037441,0.0005625015,0.00004517557,0.00001504832,0.0006164133,0.00009476974,0.00006397784],"category_scores_gemma":[0.01474148,0.00005786145,0.00006973631,0.000287298,0.0004877405,0.00007712418,0.0001921396,0.0008200153,0.000007406758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002866921,"about_ca_system_score_gemma":0.0007611156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009857139,"about_ca_topic_score_gemma":0.00002209096,"domain_scores_codex":[0.9948843,0.0005375269,0.0008207634,0.00021624,0.003104319,0.0004368424],"domain_scores_gemma":[0.9938994,0.004256715,0.0001142712,0.0001164589,0.001303295,0.0003098836],"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":[0.003875873,0.001464957,0.00755896,0.00008945591,0.0003121116,0.001872343,0.0007239406,0.002240223,0.003866892,0.8264465,0.00753315,0.1440156],"study_design_scores_gemma":[0.01302087,0.001302015,0.052536,0.006296259,0.00005988949,0.0004825201,0.001116602,0.2250727,0.0007782563,0.685159,0.01369661,0.000479257],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03215351,0.0005109557,0.9223477,0.04293355,0.0004789866,0.0001844804,0.00004669327,0.000004554976,0.001339575],"genre_scores_gemma":[0.9497736,0.002355324,0.04629072,0.0003957746,0.0009516751,0.0000353883,0.000003757189,0.0000124355,0.0001813632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9176201,"threshold_uncertainty_score":0.9935578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2654298473923808,"score_gpt":0.4474575346644549,"score_spread":0.182027687272074,"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."}}