Author Correction: Absence of CD36 alters systemic vitamin A homeostasis
Bibliographic record
Abstract
The plasma triglyceride values reported in Fig. 5A and 5D were miscalculated. The plasma retinyl ester values normalized to these plasma triglyceride values, in Fig. 5C and Fig. 5F respectively, were therefore also incorrect. In reanalysing the data, it was found that the sample size for Figure 5A and Figure 5C was insufficient, and these plots have been removed. As a result, the figure legend has been corrected. The original version of Fig. 5 and accompanying original legend appear below. Fig. 5 Circulating triglyceride and retinyl ester metabolism in wild type and Cd36 -/- mice. Postprandial A) plasma triglyceride and B) plasma retinyl ester clearance was determined in saline and p-407 injected mice. C) Retinyl esters were also normalized to plasma TG (WT Saline, n = 7; Cd36 -/- Saline, n = 6; WT p-407, n = 7; Cd36 -/- p-407, n = 5 mice per group). Hepatic VLDL D) triglyceride secretion and E) retinyl ester secretion were determined in p-407 injected mice. F) retinyl esters were normalized to triglyceride (n = 6 mice per group). Data is shown as mean ± S.D. and significance determined by two-way ANOVA (A-C; *p < 0.05 denotes a significant post-test result between genotypes within the same treatment) or Student’s t-test (D-F; ***p < 0.001). Full size image
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.128 | 0.052 |
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 source (direct Gemma or distilled Codex), 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".