Tip of the Iceberg: Part 2, Discovering What's Hidden
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
Remote storage for large collections is becoming common, making those books inaccessible for physical browsing by researchers. The main libraries at Temple University and the University of Central Florida (UCF) each have approximately 1.3 million print items on-site. Both libraries are storing 90% of their collections in automated retrieval systems with 10% remaining available for browsing in open stacks. In Part 1, “Choosing What Shows,” Karen Kohn, Temple’s Collection Analysis Librarian, describes the decisions and processes used for the 10% left physically visible. This second part explores UCF’s efforts to improve discoverability of the items in storage. The visual aspects of a book (height, multi-volume, etc.) that often provide useful clues regarding the content disappear when the patron can only view a list of search results on a computer screen. How can the loss of these visual clues be mitigated? Online browsing guides have been created at UCF to help researchers explore the hierarchical subject structure of call numbers. Other finding tools and displays may also improve awareness of stored materials.
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 | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it