What others think of us: July 1897
Bibliographic record
Abstract
For thirty years the Canadian Pharmaceutical Journal has always taken the side of the pharmacist, and since the advent of the new management and editor we have been, if anything, more pronounced than ever.During the past year we have agitated the question of cheaper alcohol, with the result that the pharmacists of Ontario and Quebec, as well as the wholesalers, followed our advice and petitioned the Government for a decrease in the import duty.Our united efforts, however, were of no avail, but our efforts resulted in arousing the druggists of Canada to appreciate the state of affairs, and if a petition was presented to the Government it was due to us, and shows that the druggists of Canada are careful readers of this journal.We have taken an active part in the agitation directed against departmental stores; and the Canadian Pharmaceutical Journal figures in the list of publications which appeared some time ago in the Toronto Evening Star as having ranged themselves on the side of the retailers, and what is more to the point, this is the only trade journal to be found in the list.The same paper published our editorial which appeared in the March issue, as expressing the opinion of the drug trade on this question.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.066 | 0.030 |
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".