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
During the “NISO update” session at the NISO Plus 2021 conference, which took place online due to the COVID-19 pandemic, members of the KBART (Knowledge Base and Related Tools) Standing Committee presented their plans and work toward KBART Phase III, a revision of the KBART Recommended Practice. In an interactive breakout session, they sought input from attendees on how KBART is being used and what new content types it should support. Presenters from the KBART Standing Committee were Noah Levin (Independent Professional), Stephanie Doellinger (OCLC, Inc.), Robert Heaton (Utah State University), and Andrée Rathemacher (University of Rhode Island). Assisting them in preparing the presentation were Jason Friedman (Canadian Research Knowledge Network), Sheri Meares (EBSCO Information Services), Benjamin Johnson (ProQuest), Elif Eryilmaz-Sigwarth (Springer Nature), and Nettie Lagace (NISO).
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.070 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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.
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