Biomarker Reconstruction of a High‐Latitude Late Paleocene to Early Eocene Coal Swamp Environment Across the PETM and ETM‐2 (Ellesmere Island, Arctic Canada)
Bibliographic record
Abstract
Abstract The Paleocene‐Eocene Thermal Maximum (PETM) and early Eocene hyperthermal events were characterized by a Hothouse climate state. Our understanding of the climatic impact of these hyperthermals is currently biased toward marine settings and the mid‐latitudes. Here we present organic geochemical data from Stenkul Fiord, Ellesmere Island, Arctic Canada. This organic rich formation was deposited in a high northern latitude wetland setting during the late Paleocene to early Eocene, spanning the PETM and subsequent ETM‐2 hyperthermals. Biomarker data (e.g., diterpenoids), combined with published palynological data from the site, indicate Cupressaceae‐dominated vegetation. Biomarkers suggest that land plant composition remained fairly unchanged across the two hyperthermal events. Increases in abundance and 13C‐depletion of hopanoid biomarkers (minima <−50‰ (VPDB)) highlight periods of enhanced bacterial methane consumption, particularly during the PETM. However, periods of low hopanoid δ13C values were also found outside the hyperthermal intervals. Relatively low δ2H values of higher plant n‐alkanes (average δ2H values of n‐C25, n‐C27, n‐C29 ∼ −230 to −270‰ (SMOW)) indicate that deposition formed during times with enhanced precipitation. The wettest intervals, as identified by the lowest δ2H n‐alkane values, contain high abundances of hopenes, indicating enhanced bacterial turnover. At Stenkul Fiord, high temperatures and CO2 concentrations likely fostered the growth of widespread wetland forests that became a CO2 sink and may have played an important role in carbon drawdown during the Early Paleogene.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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".