A YEAR FROM NOW YOU WILL WISH YOU HAD STARTED TODAY -\tREDEFINING STRATEGY AND ORGANIZATION FOR LIBRARY AUTOMATION AND CONTENT
Bibliographic record
Abstract
There is a need for a new breed of organization and strategy in a changed landscape for library systems, acquisitions and discovery. This paper presents Chalmers library re-organization and strategic viewpoint on library systems, acquisitions, collection development and development methodology based on a complete overhaul of those areas to prepare us for a changed paradigm of how library systems and media is delivered to our organization and users.\nSoftware and Data as a Service has changed the infrastructure for library automation and content delivery. Media and systems are merging in the Cloud, with vendor promise of lower total cost of ownership and demand driven acquisition solutions to ease the burden of information overload. We have passed the tipping point and these services are being rolled out to libraries globally. Chalmers University of Technology evaluated its current library automation systems and workflows with the ambition to better understand what we need from the next generation library systems and how to cope with the flood of digital content available to our users and the selection process.
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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 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".