Baseline soil composition data for the Delta Nature Reserve
Bibliographic record
Abstract
Coal trains are scheduled to pass through the Delta Nature Reserve in fall of 2015. The Burns Bog Conservation Society is concerned about the possible effects of coal contamination on the bog ecosystem. Due to this, baseline data on soil chemistry has been collected for the Delta Nature Reserve in Delta, British Columbia to study the current soil conditions. Soil samples were taken at 34 different sites around the reserve. The metal concentrations in the samples were determined using ICP-‐MS analysis, and were compared to soil standards and concentrations found in coal. Carbon and Nitrogen isotopic values were determined using isotope ratio mass spectrometry. A spatial analysis was also conducted on the Delta Nature Reserve. The results showed that soil samples exceeded the standard concentrations for lead, arsenic, copper, zinc, selenium and cobalt in some locations, based on comparison to the Canadian Council of Ministers of the Environment soil standards for agriculture and residential areas. Results did not indicate current contamination from coal. From our analysis, it can be seen that arsenic, copper, and zinc concentrations are higher closer to the train track running along the northeastern side of the reserve. The baseline data and analysis will allow the Burns Bog Conservation Society to conduct future studies on soil contamination in the reserve. This baseline data is essential because it will allow for comparison between current and future soil content as development occurs around the bog.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".