Renal Function and Bisphosphonate Safety
Bibliographic record
Abstract
We thank Dr Ott and colleagues for their letter concerning our recently published paper “Alendronate Treatment in Women with Normal to Severely Impaired Renal Function: An Analysis of the Fracture Intervention Trial”(1). Dr Ott and colleagues note that that we have misinterpreted the Kidney Diseases Outcome Quality Initiative (K/DOQI) classification(2); according to the K/DOQI classification, an estimated glomerular filtration rate (eGFR) of <30 ml/min is defined as “severe,” and in our manuscript we refer to an eGFR of <45 ml/min as severe. We recognize that using the same descriptive terms as in the KDOQI classification may be problematic. We attempted to avoid misinterpretation by clearly stating that we categorized creatinine clearance (CrCL) based on a modified Kidney Foundation classification (used in other manuscripts by our group(3)) and explicitly defined the eGFR we used: severe, <45 ml/min; moderately reduced, 45–59 ml/min; normal >60 ml/min. We chose to categorize CrCL in this manner because, as pointed out by Dr Ott and colleagues, very few women participating in the Fracture Intervention Trial had an eGFR of <30 ml/min.
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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 | 0.008 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".