Report on ICDP Deep Dust workshops: probing continental climate of the late Paleozoic icehouse–greenhouse transition and beyond
Bibliographic record
Abstract
Abstract. Chamberlin and Salisbury's assessment of the Permian a century ago captured the essence of the period: it is an interval of extremes yet one sufficiently recent to have affected a biosphere with near-modern complexity. The events of the Permian – the orogenic episodes, massive biospheric turnovers, both icehouse and greenhouse antitheses, and Mars-analog lithofacies – boggle the imagination and present us with great opportunities to explore Earth system behavior. The ICDP-funded workshops dubbed “Deep Dust,” held in Oklahoma (USA) in March 2019 (67 participants from nine countries) and Paris (France) in January 2020 (33 participants from eight countries), focused on clarifying the scientific drivers and key sites for coring continuous sections of Permian continental (loess, lacustrine, and associated) strata that preserve high-resolution records. Combined, the two workshops hosted a total of 91 participants representing 14 countries, with broad expertise. Discussions at Deep Dust 1.0 (USA) focused on the primary research questions of paleoclimate, paleoenvironments, and paleoecology of icehouse collapse and the run-up to the Great Dying and both the modern and Permian deep microbial biosphere. Auxiliary science topics included tectonics, induced seismicity, geothermal energy, and planetary science. Deep Dust 1.0 also addressed site selection as well as scientific approaches, logistical challenges, and broader impacts and included a mid-workshop field trip to view the Permian of Oklahoma. Deep Dust 2.0 focused specifically on honing the European target. The Anadarko Basin (Oklahoma) and Paris Basin (France) represent the most promising initial targets to capture complete or near-complete stratigraphic coverage through continental successions that serve as reference points for western and eastern equatorial Pangaea.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".