Registration for 4th International Evidence Based Library and Information Practice Conference
Bibliographic record
Abstract
Registration for the 4th International Evidence Based Library and Information Practice (EBLIP4) is open. The final day for registration at the reduced rate is April 9th, 2007. The conference on May 6-9, 2007 in Chapel Hill-Durham, North Carolina, will feature themed sessions on evidence-based practice in academic libraries, school library media, healthcare, special libraries, and evidence-based methodology. Two days of continuing education will follow. The conference provides a forum for the presentation of high quality papers and posters as well as examples of how EBLIP is being implemented in library and information settings around the globe. The registration form, along with further information on EBLP4, is available on the conference website at: http://www.eblip4.unc.edu/index.html.
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.014 | 0.008 |
| Insufficient payload (model declined to judge) | 0.796 | 0.604 |
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 source (direct Gemma or distilled Codex), 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".