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
Real-time heuristic search algorithms are used for planning by agents in situations where a constantbounded amount of deliberation time is required for each action regardless of the problem size. Such algorithms interleave their planning and execution to ensure real-time response. Furthermore, to guarantee completeness, they typically store improved heuristic estimates for previously expanded states. Although subsequent planning steps can benefit from updated heuristic estimates, many of the same states are expanded over and over again. Here we propose a variant of the A * algorithm, Time-Bounded A * (TBA*), that guarantees real-time response. In the domain of path-finding on videogame maps TBA * expands an order of magnitude fewer states than traditional real-time search algorithms, while finding paths of comparable quality. It reaches the same level of performance as recent state-of-the-art real-time search algorithms but, unlike these, requires neither state-space abstractions nor pre-computed pattern databases. 1
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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