Bibliographic record
Abstract
As you know the Online Journal of Rural Nursing and Health Care is a peer-reviewed journal. That means that a professional panel must review all manuscripts. This is a completely volunteer professional service. Without this effort the journal would not be the quality journal that it is. Because this work is voluntary, I am hesitant to send more than four manuscripts to any one reviewer in a year’s time. Therefore, we need a large number of reviewers to complete the work. If you would be interested in this professional service activity for the Online Journal of Rural Nursing and Health Care, please send me a note by email telling me of your area of interest and attaching your curriculum vitae. My email address is jdunkin@bama.ua.edu. Please put “Manuscript Reviewer” in the subject box so that I might efficiently respond. Thank you for assisting us in continuing to make the Online Journal of Rural Nursing and Health Care the fine e-journal that it is.It seems that every state in the United States and areas of Canada are currently facing budgetary deficits and economic hard times. That is true in Alabama as well and as a result the amount of time and effort that the Webmaster and information management staff can contribute is in serious jeopardy. It is clear that we will have to begin compensating them for their work. This is very difficult, as the journal has no revenue-generating capacity of its own, and RNO needs additional funds to provide this level of financial support to the journal.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".