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 general, a Reference Station calculates differential corrections which are valid for that exact location (zero baseline) at that particular epoch (age of corrections zero). However, DGPS users may be located as far as 200 nm away from the Reference Station and some of the errors compensated for by the Reference Station vary with space, namely satellite ephemeris, tropospheric and ionospheric errors. Therefore, the corrections calculated at the Reference Station suffer certain accuracy degradation as the separation distance increases, because of a decreasing relevance of the Reference Station data to the user. The error growth with increasing distance to the beacon is accentuated by the inability of Reference Station and user to see the same satellites, commonly termed the lack of intervisibility. The error growth with distance is the most important factor determining DGPS accuracy, but surprisingly very little has been done to assess it. US official documents and IALA state that the achievable accuracy degrades at an approximate rate of 1 m for each 150 km (80 nm) distance from the broadcast site, but this value is based on a theoretical prediction, made back in 1993. To estimate the error growth with real data, 6 DGPS receivers were placed along the Portuguese coastline at approximately 50 nm intervals from Sagres Broadcast Station, in a South – North direction. This paper describes the results of the trial.
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 | 0.001 |
| Open science | 0.000 | 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