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
In this paper, we describe a bouncing strategy (smart strategy) for a mobile robot that uses one bit of memory for feedback, and guarantees that the robot will traverse all the rooms (and doorways) of a 2D environment. The environment is modeled as a rectilinear polygon (also called orthogonal polygon), and the rooms and the doorways are defined by the decomposition algorithm we describe. Such a decomposition helps the robot to not go back to a room after leaving. We also define the notion of “virtual doors” that have the ability to let the robot through, or make the robot bounce from them. We compared three different types of bouncing rules: smart, random, billiard. The smart strategy grantees to reach to target. Although the random strategy on average behaves the same as the smart strategy, there are rectilinear polygons in which the robot cannot reach the target in the expected time steps. On the other hand, the billiard bouncing strategy can cause the robot to become trapped.
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) | 0.002 | 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