Bibliographic record
Abstract
The USGS has contracted with SPOT Image Corporation to acquire and provide Satellite Pour l'Observation de la Terre (SPOT) satellite data for November 2009 through January 2013. Under the North America Data Buy (NADB) agreements, SPOT Image will provide moderate-resolution data from their SPOT 4 and 5 satellites over the conterminous United States and parts of Canada and Mexico through the receiving capabilities at the USGS EROS Center. The French space agency, Centre National d'Etudes Spatiales (CNES), owns and operates the SPOT satellite system. SPOT Image Corporation is a subsidiary of the SPOT Image group, which provides worldwide distribution of their imagery. Under the licensing arrangements of the North America Data Buy contract, access is limited to U.S. Federal civil Government agency users and U.S. State and local government users. The 2011 contract expands usage to include U.S. tribal governments. Qualified users must be logged in to EarthExplorer to gain access to this dataset. An explanation of data restrictions and limitations is displayed when accessing these collections and must be agreed upon before gaining access to these data. The USGS SPOT 4 and 5 datasets provide North American coverage between 53 degrees north latitude and 23.5 degrees north latitude in calendar year 2010. The coverage for 2011 extends from 55 degrees north latitude to 23.5 degrees north latitude. Both SPOT satellites carry imaging instruments that operate with panchromatic and multispectral sensors. The SPOT 4 payload includes two High Resolution Visible and Infrared (HRVIR) sensors, and SPOT 5 utilizes two High Resolution Geometric (HRG) instruments. Each sensor has a swath of 60 km and has an oblique viewing capability of 27 degrees on each side of vertical. The sensors can operate independently to observe separate targets or in tandem to cover a larger swath in a single pass. Each scene in this collection is approximately 60 km by 60 km and is referenced to World Geodetic System 84 (WGS 84) datum.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.244 | 0.221 |
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".