Corrigendum: Trends in Obesity and Metabolic Status in Northern and Southern China Between 2012 and 2020
Bibliographic record
Abstract
Corrigendum on: Li Y, Yang L, Yin L, Liu Q, Wang Y, Yang P, Wang J, Chen Z, Li X, Yang Q, He Y, Huang X. (2022). Trends in Obesity and Metabolic Status in Northern and Southern China Between 2012and 2020. Front Nutr. 8:811244. doi: 10.3389/fnut.2021.In the original article, there were some mistakes in Table 1 as published. The means and SD of TG, TC, HDL-c, LDL-c, SBP, DBP and FSG in the non-obesity group were incorrect. The corrected "Table 1. Characteristics of selected study participants by obesity status" appears below. The authors apologize for those errors and state that those do not change the scientific conclusions of the article in any way. The original article has been updated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".