Bibliometric analysis of the American Journal of Veterinary Research to produce a list of core veterinary medicine journals.
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.
Bibliographic record
Abstract
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.
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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.045 | 0.157 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it