Investigation and identification of Ediacaran microbially induced sedimentary structures (MISS) in Fermeuse and Trepassey Formation, Newfoundland
Bibliographic record
Abstract
Microbially induced sedimentary structures (MISS), the physical sedimentary structures shaped and modified by microbial activities, that were abundant during Ediacaran. Their significance extends to the indicators of the depositional environments to potential hints at the contribution of microbial mats to the preservation of soft-bodied organisms. However, despite their significance, Ediacaran MISS remain understudied, with many structures yet to be confidently classified. This thesis investigates two Ediacaran MISS candidates—Arumberia and bubble trains—identified in sedimentary rocks from Musgravetown and St. John’s group in Newfoundland. Petrographic analysis, supplemented by geochemical and morphological observations, reveals that their formations are influenced by palaeocurrents and exhibit Microbially Induced Sedimentary Textures (MIST), confirming their MISS origin. Moreover, Arumberia consists of multiple morphotypes shaped by varying hydrodynamic and environmental conditions, suggesting that they worked as stimuli to form each Arumberia morphotype. Bubble trains, on the other hand, result from patchy microbial mat growth on the seafloor, which facilitates gas trapping. The accumulation of gas beneath these mats led to the formation of circular depressions at the sediment-mat interface. As such, bubble trains reflect the localised distribution of microbial mats and their role in trapping gas. By integrating sedimentological, geochemical, and morphological data, this study suggests the classification of these structures as MISS and enhances our understanding of its formation in Ediacaran environments.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".