Permafrost in the Cretaceous supergreenhouse
Bibliographic record
Abstract
During the archetypal supergreenhouse Cretaceous Earth, an active cryosphere with permafrost existed in Chinese plateau deserts (astrochonological age ca. 132.49–132.17 Ma). Permafrost wedges have been identified in three different outcrops of the Luohe Fm. Most of the wedges are concentrated in two discrete horizons bounding three draa successions representing composite-wedge pseudomorphs. A late Pleistocene analogue for the Cretaceous aeolian–permafrost system of the Luohe Fm is provided by the composite wedges and sand wedges within aeolian dune deposits of the Kittigazuit Fm., Hadwen Island, NT, Canada. A modern analogue for these Cretaceous plateau cryospheric conditions is the aeolian–permafrost system we report from the Qiongkuai Lebashi Lake area, Xinjiang Uygur Autonomous Region, China. Significantly, Cretaceous plateau permafrost was coeval with marine cryospheric indicators in the Arctic and Australia, indicating a strong coupling of the ocean–atmosphere system. The Cretaceous permafrost contained a rich microbiome at subtropical palaeolatitude and 3–4 km palaeoaltitude, analogous to recent permafrost in the western Himalayas. Global permafrost thaw during the Cretaceous released significant volumes of greenhouse gases to the atmosphere as well as dissolved organic carbon (DOC) and other nutrients into watersheds, and marine waters affecting aquatic systems through carbon and nutrient additions. The contribution of permafrost thaw to the Cretaceous global C balance, including during oceanic anoxic events (OAE) will have to be determined in future research dealing with ocean–continental cryosphere coupling associated with events of cryosphere degradation in the aftermaths of supergreenhouse cold snaps. A mindset of persistent ice-free greenhouse conditions during the Cretaceous has stifled consideration of permafrost thaw as a contributor of C and nutrients to the palaeo-oceans and palaeo-atmosphere.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".