Bibliographic record
Abstract
Recent pharmaceutical controversies have awakened the public from their "drug-induced" slumber.The dream of "miracle" drugs has been shattered with product recalls, warning labels and study results.In light of these events, the public has become more vigilant and cautious.But how long will it be before society is lulled back into gentle complacency by the colourful advertisements of "big pharma"?Shama Sud examines the history of pharmaceutical tragedies from an ethical perspective in her article.To complement this discussion, Sammy Ali provides the science behind why Vioxx, a popular arthritis drug, was deemed unsafe.This issue of the McMaster Meducator also addresses a variety of other medical research topics.Danny Ricci discusses traditional and alternative therapies for Alzheimer's disease.Waqas Kayani reviews the current research in the field of CNS repair through remyelination.Andrew Heikkila explains the pathology of hepatocellular carcinoma (liver cancer).Finally, Abdullah Alabousi introduces readers to a life without pain in his discussion of CIPA (Congenital Insensitivity to Pain with Anhidrosis).
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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.022 | 0.020 |
| Insufficient payload (model declined to judge) | 0.020 | 0.013 |
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".