NRI Benthic Invertebrate Monitoring Program Ecological Integrity of Arctic Streams
Bibliographic record
Abstract
Objectives: To assess and identify the extent of long-term biological impairment from multiple stressors in the streams and rivers of the South-Baffin region of Nunavut. Outline: Arctic freshwater streams and rivers are highly specialized systems that are susceptible to a wide variety of anthropogenic disturbances. The examination of bio-indicators that respond to changes in temperature, dissolved oxygen, nutrients, and pollutants can thus be used to infer the overall health of these systems. In order to establish a long-term monitoring program to assess the ecological integrity of these systems, these indicators are used to determine any deviation from the established baseline conditions. Since most monitoring protocols in use are based off of research in southern temperate systems, the assessment of Arctic tundra streams requires the development of predictive reference model. As there are also no measures of what a ‘pristine ’ habitat is, a reference condition approach is necessary to determine the baseline conditions of the benthic invertebrate communities of undisturbed streams. While the reference condition approach will require a large sampling commitment for the initial assessment phase, it will allow for the selection of parameters to use in an index which is ecologically significant as well as and based off of the predictive model developed from the reference conditions of ‘pristine ’ tundra streams. Thus, comparing ‘pristine ’ and ‘disturbed’
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".