Anthropogenic versus climatic control in a high-resolution 1500-year chironomid stratigraphy from a southwestern Greenland lake
Bibliographic record
Abstract
Abstract We performed a high-resolution study of chironomid assemblages in a sediment core retrieved from Lake Igaliku in southern Greenland. The well-dated core is located within the former Norse Eastern Settlement and covered the last 1500 yr. The comparison of chironomid stratigraphy (PCA axis scores) with instrumental temperature data, land use history and organic matter in the sediment over the last 140 yr suggested that the primary changes in chironomid fauna in 1988 ± 2 yr were driven by the shift to modern agriculture in the catchment. This unprecedented change in chironomid fauna was most likely triggered by a shift in in-lake processes. Within the instrumental period, subtle variations in the chironomid assemblages that occurred before 1988 ± 2 yr were significantly correlated with summer temperatures even in times of traditional extensive sheep farming in the catchment. The relevance of the chironomid-derived climate signal over the last 1500 yr was supported by its good concordance with previous studies in west Greenland and in the Arctic. The chironomid assemblage therefore appeared to be a valuable proxy for climate changes within the Norse colony area. Synchronous changes in Norse diet and chironomid-reconstructed climate give new insights into the interplay of Norse society with climate.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".