An organic geochemical reconstruction of North American temperature gradients over the Cretaceous-Paleogene boundary
Bibliographic record
Abstract
Latitudinal temperature gradients are a critical component of the climate system and control the transport of heat and moisture. However, this process is poorly understood during past intervals of extreme greenhouse climate, in particular owing to models suggesting that gradients must be much steeper than proxy data imply. Palaeotemperature records Late Cretaceous–Early Paleogene can provide insight into how the global climate system operates under greenhouse conditions. Much of our understanding of palaeotemperatures and gradients therein during this interval comes from marine sea-surface temperature proxy data, with very few terrestrial records. These palaeoclimate reconstructions are hampered by poor temporal resolution, difficulties in correlating between sites, and limited spatial coverage. Lipids from fossil peats across North America provide an opportunity to investigate terrestrial palaeotemperatures across the Cretaceous–Paleogene boundary and how these differ across a range of latitudes. Here we present a mean annual air temperature record spanning this interval from the Canadian High Arctic (~75°N palaeolatitude). Our data show that temperatures ranged from 0–18°C, compared with 13–27°C at contemporaneous peat-accumulating sites in Saskatchewan (~60°N palaeolatitude). These data indicate a temperature gradient of approximately 10°C. These values are similar to those modelled for the latest Cretaceous, and the latitudinal difference is comparable to the modern gradient across North America (UCAR), albeit ~20°C warmer. Our study demonstrates that although the Arctic experienced high terrestrial temperatures, the K-Pg interval saw a well-defined latitudinal temperature gradient. Further, our reconstructions fill an existing gap in the terrestrial record and highlight the value of fossil peats in palaeoclimate studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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) | 0.002 | 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".