MétaCan
Menu
Back to cohort
Record W2129973888 · doi:10.18438/b81w4j

The Impact of the Acquisition of Electronic Medical Texts on the Usage of Equivalent Print Books in an Academic Medical Library

2010· article· en· W2129973888 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEvidence Based Library and Information Practice · 2010
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsElectronic bookComputer scienceVendorElectronic journalCollection developmentWorld Wide WebUsage dataBusiness

Abstract

fetched live from OpenAlex

Objectives – This study examines whether acquiring a text in electronic format effects the usage of the print version of the text, focusing specifically on medical texts. Studies in the literature dealt specifically with general collections and it was not clear if they were applicable to medical collections. It was also not clear if these studies should play a role in determining whether a medical library should purchase electronic texts or whether reserve collections are still needed for print texts. Methods – Four usage studies were conducted using data from the circulation system and the electronic vendor systems. These were 1) trends of print usage; 2) trends of electronic usage; 3) a comparison of electronic usage with print usage of the same title in the reserve collection; 4) a comparison of electronic usage with print usage of the same title in the general collection. Results – In comparison to print, substantial usage is being made of electronic books. Print is maintaining a level pattern of usage while electronic usage is increasing steadily. There was a noticeable difference in the usage levels of the electronic texts as regards to the package in which they are contained. Usage of print texts both on reserve and in the general collection has decreased over time, however the acquisition of the electronic version of a medical title had little impact on the usage of the equivalent print version. Conclusion – There is a demand for medical texts in medical libraries. Electronic versions can replace print versions of texts in reserve. Further investigation is needed of current patterns of print collection usage, with particular emphasis on trends in reserve collection usage.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptScholarly communication
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.922
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.082
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.274
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it