The Availability of MeSH in Vendor-Supplied Cataloguing Records, as Seen Through the Catalogue of a Canadian Academic Health Library
Bibliographic record
Abstract
This study examines the prevalence of medical subject headings in vendorsupplied cataloguing records for publications contained within aggregated databases or publisher collections.In the first phase, the catalogue of one Canadian academic medical library was examined to determine the extent to which medical subject headings (MeSH) are available in the vendor-supplied records.In the second phase, these results were compared to the catalogues of other Canadian academic medical libraries in order to reach a generalization regarding the availability of MeSH headings for electronic resources.MeSH was more widespread in records for electronic journals but was noticeably lacking in records for electronic monographs, and for Canadian publications.There is no standard for ensuring MeSH are assigned to monograph records for health titles and there is no library in Canada with responsibility for ensuring that Canadian health publications receive Medical Subject Headings.It is incumbent upon libraries using MeSH to ensure that vendors are aware of this need when purchasing record sets.
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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 | 0.012 | 0.116 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.056 | 0.116 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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; 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".