From controversy to consensus: making the case for recent climate change in the Arctic using lake sediments
Bibliographic record
Abstract
We live in a constantly changing environment, yet tracking ecological change is often very difficult. Long-term monitoring data are frequently lacking and are especially sparse from Arctic ecosystems, where logistical difficulties limit most monitoring programs. Fortunately, lake and pond sediments contain important archives of past limnological communities that can be used to reconstruct environmental change. Here, we summarize some of the paleolimnological studies that have documented recent climate warming in Arctic lakes and ponds. Several hypotheses have been evaluated to determine if warming, resulting in changes in ice cover and related variables (eg increased habitat availability), was the factor most strongly influencing recent diatom and other biotic changes. Striking and often unprecedented community changes were evident in post-1850 sediments, and could be linked to ecological shifts consistent with warming. Because future temperature increases are predicted to be greatly amplified in polar regions, the ecological integrity of these sensitive ecosystems will be further imperiled.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".