The Oligocene-Miocene Transition : new insights from the Newfoundland Margin
Bibliographic record
Abstract
As a major site of deep water formation, the North Atlantic plays a critical role in global climate. To understand better how Earth’s climate system works it should therefore be a priority for geologists to study the record of past climate change encoded in the sedimentary archives that accumulate in the deep Atlantic. Here, sediment drilled in several cores on the Newfoundland Margin by International Ocean Discovery Program (IODP) Expedition 342 is utilized to provide fresh insights into palaeoclimate history, focusing on one of the more enigmatic events of the Cenozoic: the Oligocene-Miocene Transition (OMT), 23 million years ago. This is a time interval that Expedition 342 sediments have recorded in an continuous and expanded fashion unparalleled in previous records. This thesis aims to shed new light on North Atlantic OMT climate variability on both orbital and millennial-centennial timescales, and to increase the fidelity of foraminiferal proxies in this time interval. In Chapter 3, late Oligocene climate is shown to change cyclically on sub-orbital timescales. Centennial-millennial timescale variability is a key feature of Plio- Pleistocene climate; the record presented here is the first such record from earlier in the Cenozoic. These results show that Atlantic meridional overturning circulation is variable on sub-orbital timescales over a wider range of climate states than previously recognized. In Chapter 4, orbital- resolution planktic stable isotope records spanning the OMT are presented. These results – the first orbital-timescale record of sea surface conditions over the OMT – reveal that temperature changes in North Atlantic surface waters precede Antarctic glaciation/deglaciation and bottom water cooling/warming by tens of kyrs. In Chapter 5, the excellent preservation quality of foraminifera recovered by IODP Expedition 342 is exploited in a rigorous assessment of the taxonomy of several planktic foraminiferal species often used to generate palaeoclimate records over the OMT, with a focus on Globigerina bulloides. This quantitative, statistical approach enables non- subjective delineation of morphological variability into morphospecies, and highlights subtle morphological features that are critical to distinguish when picking foraminifera for stable isotope analyses. Together, the results of this thesis reveal that Earth’s climate system in the late Oligocene to early Miocene was much more dynamic and complex than previously recognized.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".