Bibliographic record
Abstract
At Marion General Hospital in Indiana, an increase in the cost of one component of the facility’s gastrointestinal (GI) “cocktail” prompted a review of the usefulness of that medication and an evidence-based change to the compounded admixture. Clinical pharmacist Elaine Greene, clinical programs facilitator, said emergency department (ED) physicians at the 99-bed not-for-profit hospital had been ordering GI cocktails that consisted of a compounded mixture of viscous lidocaine, an antacid, and Donnatal elixir. Donnatal contains phenobarbital, hyoscyamine sulfate, atropine sulfate, and scopolamine hydrobromide. The product is marketed by Concordia Pharmaceuticals Inc., a West Indies–based subsidiary of Concordia Healthcare Corp. of Ontario, Canada. Concordia acquired the Donnatal product line in 2014 from Revive Pharmaceuticals (formerly PBM Pharmaceuticals) of Charlottesville, Virginia. Greene said that after a noticeable increase in the price of Donnatal, she looked for scientific literature about the effectiveness of GI cocktails. She wasn’t surprised by what she discovered. “A couple of articles … seemed to imply that there was not a lot of benefit beyond the antacid,” Greene said.
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 | 0.043 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".