Significantly warmer Arctic surface temperatures during the Pliocene indicated by multiple independent proxies
Bibliographic record
Abstract
Temperatures in the Arctic have increased by an astounding 1 °C in response to anthropogenic forcing over the past 20 years and are expected to rise further in the coming decades. The Pliocene (2.6-5.3 Ma) is of particular interest as an analog for future warming because global temperatures were significantly warmer than today for a sustained period of time, with continental configurations similar to present. Here, we estimate mean annual temperature (MAT) based upon three independent proxies from an early Pliocene peat deposit in the Canadian High Arctic. Our proxies, including oxygen isotopes and annual ring widths (MAT =-0.5 ± 1.9 °C), coexistence of paleovegetation (MAT =-0.4 ± 4.1 °C), and bacterial tetraether composition in paleosols (MAT =-0.6 ± 5.0 °C), yield es
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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 | 0.001 |
| 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".