Digital elevation model and shaded relief map
Bibliographic record
Abstract
The Canadian Digital Elevation Data, Level 1 (CDED1) consists of an ordered array of ground elevations at regularly spaced intervals. The CDED1 is based on National Topographic Data Base (NTDB) digital files at scales of 1:50 000 and 1:250 000 or various scaled positional data acquired from the provinces, according to the National Topographic System (NTS). The coverage for every file corresponds to half an NTS map, which means that there are western and eastern parts to the CDED1 for each NTS map. The grid spacing is based on geographic coordinates at a maximum and minimum resolution of 0.75 and 3 arc seconds for the 1:50 000, and 3 and 12 arc seconds for the 1:250 000 respectively, depending on latitude. A CDED1 file consists of elevation data recorded in metres relative to Mean Sea Level (MSL) based on the North American Datum 1983 (NAD83) horizontal reference datum. The Centre for Topographic Information (CTI) jointly produces the CDED1 with federal and provincial government agencies and the private sector, using terrain-modelling software. CDED1 files are delivered in ASCII format for either DOS or UNIX operating systems and are available via the File Transfer Protocol (FTP). The data should be compatible with all translators designed for the United States Geological Survey (USGS) Digital Terrain Elevation Data (DTED). The files are compressed using the PKZIP compression software. The shaded relief image is created from the The Canadian Digital Elevation Data, Level 1 (CDED1) which consists of an ordered array of ground elevations at regularly spaced intervals. The CDED1 is based on National Topographic Data Base (NTDB) digital files at scales of 1:50 000 and 1:250 000 or various scaled positional data acquired from the provinces, according to the National Topographic System (NTS). The shaded relief image gives a simulated appearance of the sun shining on the terrane at a specific azimuth and altitude.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.070 | 0.038 |
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".