Profundal-Pelagic Macrocrustacean Abundance in Boreal Lakes Before and After Experimental Clearcut Logging
Bibliographic record
Abstract
A sampling program of 9 years revealed that the opossum shrimp Mysis relicta and the amphipod Diporeia hoyi were present in three boreal lakes in northwestern Ontario, Canada regardless of whether watershed forests were left completely intact, left as only a narrow buffer strip, or were nearly completely removed through experimental clearcutting. In fact, Diporeia were actually found to be more abundant in all lakes following logging. And the decline in Mysis abundance observed in one of the lakes occurred well before the initiation of timber removal. Consequently, it appears that these keystone, glacial-relic species of macrocrustaceans are not negatively impacted by clearcutting. This is in direct contrast to the hyper-sensitivity and extirpation of these same species which has been previously demonstrated in acidifying boreal lakes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".