Bibliographic record
Abstract
Appleton, Wisconsin, US-November 11, 2014-American Digital Cartography, Inc., a leader in providing comprehensive, current and seamless geographic digital data for the whole earth, is pleased to announce the release of ADC WorldMap Digital Atlas v7.1.The ADC WorldMap upgrade features two new layers: World Seas and World Coastlines.The World Seas layer represents seas for the entire world represented as polygons.The World Coastlines layer contains coastlines for the entire world, differentiated by country.With the addition of these two new layers, this release of ADC WorldMap will con tain a total of 42 detail-rich layers and tables.Along with the two new layers, ADC WorldMap Digital Atlas v7.1 includes current country and first level political boundaries for the entire world and over 37 000 second level political boundaries in 123 countries.The population data has also been updated in many cities across 112 countries.This release also adds over 2 300 parks to the Parks and Protected Areas layers.Joe Roehl, Vice President of ADCi, says, "We continually look to enhance the features included in ADC WorldMap by staying current with market needs."Roehl adds, "Version 7.1 adds two new layers-World Seas and World Coastlines-which further enhances the best available worldwide data at this scale."ADC WorldMap Digital Atlas v7.1 is available in Esri, MapInfo and Oracle Spatial formats. MapQuest Becomes First Navigation App to Offer On-demand Roadside Assistance
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.493 | 0.435 |
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".