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
With the proliferation of mobile devices in both smartphone and tablet form factors, it is intuitive and natural for users to socially interact with their collaborators or competitors in multi-party conferencing, productivity, or gaming applications. In this paper, we make a case that such social interactions should be much more spontaneous to users in these applications. We design and implement a new system framework, Reflex, to provide the required system support to achieve spontaneous social interaction with other users in the same mobile application, be they in the same living room or around the world. Reflex features a simple and intuitive application programming interface (API), and uses cloud computing services from Google App Engine to offer the scalability and performance required to support spontaneous social networking at a large scale. Reflex is able to transparently switch to local interactions over Bluetooth or Wi-Fi interfaces, available on mobile devices, whenever possible. In order to evaluate Reflex in the iOS platform, we developed a real-world music composition application, called MusicScore, from scratch on the iPad, which takes advantage of Reflex to let music composers collaborate in real time.
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