EnviroAtlas - Atmospheric Nitrogen Deposition by 12-digit HUC for the Conterminous United States (2002)
Bibliographic record
Abstract
this enviroatlas dataset includes annual nitrogen and sulfur deposition within each 12 digit huc subwatershed for the year 2002 values are provided for total oxidized nitrogen hno3 no no2 n2o5 nh3 hono pan organic nitrogen and particulate no3 oxidized nitrogen wet deposition oxidized nitrogen dry deposition total reduced nitrogen nh3 and particulate nh4 reduced nitrogen dry deposition reduced nitrogen wet deposition total dry nitrogen deposition total wet nitrogen deposition total nitrogen deposition wet dry total sulfur so2 particulate so4 dry deposition total sulfur wet deposition and total sulfur deposition the dataset is based on output from the community multiscale air quality modeling system cmaq v5 0 2 run using the bidirectional flux option for the 12 km grid size for the us canada and mexico the cmaq output has been post processed to adjust the wet deposition for errors in the location and amount of precipitation and for regional biases in the tno3 hno3 no3 nhx nh4 nh3 and sulfate wet deposition model predicted values of dry deposition were not adjusted this dataset was produced by the us epa to support research and online mapping activities related to enviroatlas enviroatlas https www epa gov enviroatlas allows the user to interact with a web based easy to use mapping application to view and analyze multiple ecosystem services for the contiguous united states the dataset is available as downloadable data https edg epa gov data public ord enviroatlas or as an enviroatlas map service additional descriptive information about each attribute in this dataset can be found in its associated enviroatlas fact sheet https www epa gov enviroatlas enviroatlas fact sheets
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.018 |
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".