Chironomid-inferred postglacial temperature reconstruction from Gold Lake, Oregon, USA
Bibliographic record
Abstract
Abstract A paleotemperature reconstruction inferred from subfossil chironomid (non-biting midge) assemblages in a 13-meter, 14,500-yr lake sediment record from a montane forest in the Pacific Northwest is compared to existing quantitative temperature reconstructions from the Pacific Northwest. With updated temperatures, a regional training set was used to develop a midge-based mean July air temperature (MJAT) inference model (r2jack = 0.71, root mean square error of prediction = 1.09°C). The average inferred MJAT varied between 9.4°C and 13.2°C. During the late-glacial period, MJAT ranged between 9.4°C and 10.8°C, and the lowest MJAT (9.4°C) is inferred at ca. 12.7 ka during the Younger Dryas. The transition into the Early Holocene was marked by an increase from 11°C at 11 ka to 12°C at 9.2 ka. Following deposition of the Mazama tephra, chironomid concentration decreased rapidly, and MJAT rose to 12.3°C at ca. 7.6 ka. This change in chironomid assemblage may be due to the direct effects of the tephra on the surface energy balance. The reconstructed temperature did not track decreasing Holocene summer insolation but instead revealed Late Holocene warming, which is similar to a chironomid reconstruction in the eastern Sierra Nevada and a sea-surface temperature reconstruction from northern California.
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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".