Endogenous Parathyroid Hormone–Related Protein Compensates for the Absence of Parathyroid Hormone in Promoting Bone Accrual In Vivo in a Model of Bone Marrow Ablation
Bibliographic record
Abstract
A reader of the JBMR informed the editors about concern regarding two figures in the article Zhu and colleagues.1 In consultation with the Committee on Publication Ethics (COPE) guidelines, the editors sought an explanation from the authors. In Zhu and colleagues1 the authors acknowledge an error made in Fig. 3A by including the original 4,6-diamidino-2-phenylindole (DAPI) and TUNEL microscopic fields for the 1-week and 2-week images (not 2-week and 4-week). The authors provided a corrected version of Fig. 3, which contains images that are representative of the results shown in the graph, where the percentage of TUNEL+ cells is quite different at 1 and 2 weeks in WT mice. In Zhu and colleagues1 the authors also acknowledge an error made in Fig. 5G, by including the original calcium sensing receptor (CaSR)-positive microscopic fields for the 5-day and 1-week images. The authors were able to locate an alternative image showing WT at 5 days. The amended Fig. 5 contains an image of CaSR immunohistochemistry in WT mice that still clearly distinguishes CaSR immunopositive cells at 5 days in WT and PTH–/– mice as shown in the graph. Both revised figures appear below, and the authors regret any confusion and inconvenience this may have caused the readers of the JBMR. Fig. 3 Fig. 5
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.008 |
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".