Paleogene Paleohydrology of Ellesmere and Axel Heiberg Islands (Arctic Canada) From Palustrine Carbonates
Bibliographic record
Abstract
Abstract Ancient greenhouse periods are useful analogs for predicting effects of anthropogenic climate change on regional and global temperature and precipitation patterns. A paucity of terrestrial data from polar regions during warm episodes challenges our understanding of polar climate responses to natural/anthropogenic change and therefore our ability to predict future changes in precipitation. Ellesmere and Axel Heiberg Islands in the Canadian Arctic preserve terrestrial deposits spanning the late Paleocene to middle Eocene (59–45 Ma). Here we expand on existing regional sedimentology and paleontology through the addition of stable (δ13C, δ18O) and clumped (Δ47) isotope analyses on palustrine carbonates. δ13C isotope values range from −4.6 to +12.3‰ (VPDB), and δ18O isotope values range from −23.1 to −15.2‰ (VPDB). Both carbon and oxygen isotope averages decrease with increasing diagenetic alteration. Unusually enriched carbon isotope (δ13C) values suggest that analyzed carbonates experienced repeated dissolution‐precipitation enrichment cycles, potentially caused by seasonal fluctuations in water availability resulting in summer carbonate dissolution followed by winter carbonate re‐precipitation. Stable isotopes suggest some degree of precipitation seasonality or reduction in winter water availability in the Canadian Arctic during the Paleogene. Clumped (Δ47) temperature estimates range from 52 to 121°C and indicate low temperature solid‐state reordering of micritic samples and diagenetic recrystallization in sparry samples. Average temperatures agree with vitrinite reflectance data for Eureka Sound Group and underlying sediments, highlighting structural complexity across the region. Broadly, combined stable and clumped isotope data from carbonates in complex systems are effective for describing both paleoclimatic and post‐burial conditions.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 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".