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
Remotely instructing and guiding users in physical tasks has offered promise across a wide variety of domains. While it has been the subject of many research projects, current approaches are often limited in the communication bandwidth (lacking context, spatial information) or interactivity (unidirectional, asynchronous) between the expert and the learner. Systems that use Mixed-Reality systems for this purpose have rigid configurations for the expert and the learner. We explore the design space of bi-directional mixed-reality telepresence systems for teaching physical tasks, and present Loki, a novel system which explores the various dimensions of this space. Loki leverages video, audio and spatial capture along with mixed-reality presentation methods to allow users to explore and annotate the local and remote environments, and record and review their own performance as well as their peer's. The system design of Loki also enables easy transitions between different configurations within the explored design space. We validate its utility through a varied set of scenarios and a qualitative user study.
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 | 0.005 |
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