New insights on Late Pliensbachian-Early Toarcian seawater chemistry based on belemnite rostra element content
Bibliographic record
Abstract
Belemnites were a type of cephalopod abundant in the Jurassic and Cretaceous, whose fossils have been extensively used for paleo-oceanographic studies. For this study, we analyzed 69 elements by Inductively Coupled Plasma-Sector Field Mass Spectrometry (ICP-SFMS) in 15 belemnite rostra from the West Rodiles section in the Asturian Basin, Northern Spain. We aim to determine if belemnite rostra carbonate chemistry reflects changes in seawater chemistry during the Late Pliensbachian–Early Toarcian time interval and examine how belemnites can be used to trace known drivers of the Early Toarcian Oceanic Anoxic Event (T-OAE) and associated oceanographic processes. Discarding drastic intra-species effects and assuming a similar influence of growth rates, diet, and other physiological processes for all analyzed belemnite specimens and taking into consideration the sizeable analytical uncertainty, we assess if determined belemnite rostra element chemistry reflects broad and relative changes in paleo-seawater chemistry. Many determined elements are present in only ppb amounts, and their interpretation is uncertain. We found that Mg, Mn, and P increase in the interval chronocorrelative to the T-OAE. This is interpreted to have resulted from an increase in these elements' inventory in seawater due to an increase in continental weathering and fluvial runoff associated with this global event. Iron, K, and Na contents decrease upwards in the section, potentially indicating that these elements became limited and likely hampered oceanic productivity. Our study also found a correspondence between a change in the behaviour of several elements, warming, the T-OAE negative CIE, and a reduction in the diversity and size of both calcareous nannofossils and belemnites in the study area.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".