ASSESSING HORIZONTAL POSITIONAL ACCURACY OF
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
The horizontal positional accuracy of Google Earth is assessed in the city of Montreal, Canada, using the precise coordinates of ten GPS points spatially distributed all over the city. The results show that the positional accuracy varies in the study area between ∼0.1 m in the south to ∼2.7 m in the north. Furthermore, two methods are developed for correcting the observed positional errors: (a) using a set of transformation parameters between true coordinates of the geodetic points and their coordinates in Google Earth, and by (b) interpolating the misfit vectors at the geodetic points. The former method reduces the overall accuracy to ∼67 cm RMSE, whereas the latter one practically removes all the distortion (RMSE = 1 cm). Both methods can be developed for other places in the world subject to availability of appropriate control points. In addition, a displacement problem caused by the topography of the area and the viewing angle of the imaging satellite is discussed, and it is shown that the true positions can be shifted even up to several meters, as a consequence.
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 | 0.000 |
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