EDI Pilot Project Steering CommitteeFinal Report and Recommendations
Bibliographic record
Abstract
Before 2006 the University Library received about 180,000 paper slips annually from six different approval vendors: Coutts, Blackwell, YBP/Lindsay & Croft, Harrassowitz, Touzot, and Casalini Libri. In May 2006 a steering committee was struck to determine how to move Selection & Acquisitions processes into an electronic environment. By mid‐2007 we had successfully implemented electronic slips and 9xx/EDI ordering with our three major vendors, two of whom had never worked with a SirsiDynix customer before. In late 2007 the EDI committee began to explore WorldCat Selection, which was implemented in 2008. This system includes slips from our three major vendors, as well as our smaller specialty vendors. It took almost a year to get all of the vendors properly configured and working to our satisfaction. Memorial was the first Canadian university to adopt WorldCat Selection, which provided us an opportunity to help OCLC shape and refine the system. This report provides a detailed look the EDI implementation process, including the findings of the committee, and our final recommendations for streamlining workflow.
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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 | 0.108 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.075 | 0.051 |
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".