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
Applications that perform continuous sensing on mobile phones have the potential to revolutionize everyday life. Examples range from medical and health monitoring applications, such as pedometers and fall detectors, to participatory sensing applications, such as noise pollution, traffic and seismic activity monitoring. Unfortunately, current mobile devices are a poor match for continuous sensing applications as they require the device to remain awake for extended periods of time, resulting in poor battery life. We present Sidewinder, a new approach toward offloading sensor data processing to a lowpower processor and waking up the main processor when events of interest occur. Sidewinder differs from other heterogeneous architectures in that developers are presented with a programming interface that lets them construct custom wake-up conditions by linking together and parameterizing predefined sensor data processing algorithms. Sidewinder's wake-up conditions achieve energy efficiency matching fully programmable offloading, but do so with a much simpler programming interface that facilitates deployment and portability.
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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.003 |
| 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