Diatom reference communities in Québec (Canada) streams based on Kohonen self-organizing maps and multivariate analyses
Bibliographic record
Abstract
The identification of biological reference conditions specific to each type of water body is essential for the development of sound biological indicators and criteria. The purpose of the present study was to establish the reference conditions of each stream type sampled in southern Québec (Canada) using benthic diatoms and environmental variables characterizing streams and watersheds. First, stream reaches were classified as a function of their natural watershed and habitat characteristics. Second, diatom communities were classified based solely on taxa abundance data. Resulting groups were graphically presented on ordinations to interpret, a posteriori, the environmental gradients associated with diatom groups and to identify the diatom communities representing the reference conditions of each of the stream reach groups. A final classification based solely on diatom reference communities found pH and conductivity to be the main discriminating factors, regardless of ecoregion and stream type. Although a specific diatom reference community may be identified for each stream group, our results suggest that many of these communities exhibit strong similarities. Only two reference communities may therefore be used, one for circumneutral conditions and one for alkaline conditions. These reference communities represent the baseline for biocriteria development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".