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
The Integrated Laboratory Network (ILN) is an initiative to provide anytime, anyplace access to advanced scientific instrumentation and online laboratories for science education. To date, the ILN has been used successfully in high schools, community colleges, and universities, both nationally and internationally, and has provided new learning opportunities that incorporate instrumentation into the broader curriculum. The ILN uses open source software to facilitate remote access to instrumentation and curricular materials and to support video conferencing during online laboratory sessions. This chapter describes the principles and best practices of the ILN. Specifically, the history of the ILN, the technologies used by the ILN, and the pedagogical issues and strategies related to the design, implementation, delivery, and evaluation of online ILN labs will be discussed. Current activities toward the development of laboratory science kits enhanced with remote instrumentation and the formation of an international consortium of online laboratory developers will also be presented.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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