All Across the Circle: Using Auto-Ordering to Improve Object Transfer between Mobile Devices
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
People frequently form small groups in many social and professional situations: from conference attendees meeting at a coffee break, to siblings gathering at a family barbecue. These ad-hoc gatherings typically form into predictable geometries based on circles or circular arcs (called F-Formations). Because our lives are increasingly stored and represented by data on handheld devices, the desire to be able to share digital objects while in these groupings has increased. Using the relative position in these groups to facilitate file sharing can enable intuitive techniques such as passing or flicking. However, there is no reliable, lightweight, ad-hoc technology for detecting and representing relative locations around a circle. In this paper, we present two systems that can auto-order locations about a circle based on sensors that are standard on commodity smartphones. We tested these systems using an object-passing task in a laboratory environment against unordered and proximity-based systems, and show that our techniques are faster, are more accurate, and are preferred by users.
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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 | 0.001 |
| 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