Bibliographic record
Abstract
Suspicions about the validity of research by Professor Ranjit Kumar Chandra, a prominent Canadian researcher, have been raised by three journals, including the BMJ . The latest concern, in an editorial and a letter in the November issue of Nutrition (2003;19: 955-6 and 976-80) question research published in that journal by Professor Chandra in September 2001 (17:709-12). The Nutrition study was a randomised, blind, placebo controlled trial. It showed that a specific multivitamin and mineral supplement could improve cognitive function in people aged over 65 years. Professor Chandra, who was the sole author, concluded that the supplement might delay the onset of Alzheimer's disease. The original paper and the most recent letter and editorial questioning its validity have attracted considerable media attention. > The BMJ's statistical reviewer concluded that the data had “all the hallmarks of being entirely invented.” The 2001 paper in Nutrition is almost identical to a paper submitted to the BMJ in October 2000, which followed up a trial published in the Lancet in 1992 (340: 1124-7) The BMJ paper was not published because of serious problems identified during peer review. These problems included the lengthy period between the Lancet trial and submission of the manuscript on the same set of data to the BMJ and doubts that a major trial could have been undertaken by one man, who, …
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 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 | 0.335 | 0.748 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.018 | 0.031 |
| Scholarly communication | 0.028 | 0.011 |
| Open science | 0.012 | 0.011 |
| Research integrity | 0.051 | 0.044 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".