Bibliographic record
Abstract
This article contributes to the clarification of the coordinate reference systems (CRS) used by some Web mapping applications. This is a complex issue, mainly because of a lack of pertinent information; there is little published literature on CRS, and information available online – which is not produced by mapping experts – is fragmented and often imprecise. Following a short introduction focusing on Web mapping and the European Petroleum Survey Group (EPSG) database, which is currently maintained and published by the International Association of Oil and Gas Producers (OGP) Geomatics Committee, the article analyzes the CRS used by some well-known Web mapping applications, such as Google Maps and Bing Maps (planimetric browsers) and Google Earth (virtual globe). Some geodetic technical information is given, with reference to the main desktop GIS software libraries and to reports on CRS queried from different versions of the EPSG database (2008–2013).
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.013 | 0.026 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".