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Record W1519442902

Bibliometric analysis of the American Journal of Veterinary Research to produce a list of core veterinary medicine journals.

2006· article· en· W1519442902 on OpenAlexaff
Jill Crawley-Low

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsVeterinary medicineBibliometricsMedicineLibrary scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: Bibliometric techniques were used to analyze the citation patterns of researchers publishing in the American Journal of Veterinary Research (AJVR). METHODS: The more than 25,000 bibliographic references appearing in the AJVR from 2001 to 2003 were examined for material type, date of publication, and frequency of journals cited. Journal titles were ranked in decreasing order of productivity to create a core list of journals most frequently used by veterinary medical researchers. RESULTS: The majority of items cited were journals (88.8%), followed by books (9.8%) and gray literature (2.1%). Current sources of information were favored; 65% of the journals and 77% of the books were published in 1990 or later. Dividing the cited articles into 3 even zones revealed that 24 journals produced 7,361 cited articles in the first zone. One hundred thirty-nine journals were responsible for 7,414 cited articles in zone 2, and 1,409 journals produced 7,422 cited articles in zone 3. CONCLUSIONS: A core collection of veterinary medicine journals would include 49 veterinary medicine journals from zones 1 and 2. Libraries supporting a veterinary curriculum or veterinary research should also include veterinary medical journals from Zone 3, as well as provide access to journals in non-veterinary subjects such as biochemistry, virology, orthopedics, and surgery and a selection of general science and medical journals.

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

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
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.056
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.1370.155
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.002

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.

Opus teacher head0.642
GPT teacher head0.587
Teacher spread0.055 · 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

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations52
Published2006
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicVeterinary Practice and Education StudiesCategoryBibliometricsFrench-language works237,207