EXPERIMENTAL FORMATION OF A MICROBIAL DEATH MASK
Bibliographic record
Abstract
Abstract This study represents a first attempt to observe soft-tissue decay in association with microbial mats, in order to recreate the death-mask model proposed for terminal Neoproterozoic Lagerstätten. This model explains the precipitation of authigenic iron sulfide minerals on, and around, decaying carcasses in association with microbial mats, cementing the sediment as a sole veneer and retaining the external morphology of the organism in relief on the upper and lower surface of coarse-grained sandy event beds. Although this model has been substantiated by the discovery of abundant microbially induced sedimentary structures (MISS) and pyrite veneers in close association with Ediacaran fossils, it has not been tested previously by experimental taphonomic studies under controlled laboratory conditions. Arthropod larvae that decayed on top of a cyanobacterial mat demonstrated higher quality preservation of fine-scale anatomy than larvae that decayed in the absence of a mat. Decay experiments involving bacterial mats and organic-rich sands generated a black ring extending radially from the decaying carcasses. When this precipitate was analyzed using XPS and ESEM-EDS it revealed the presence of likely iron sulfides, or at least spatially associated Fe and S, and localized concentrations of common aluminosilicate elements (Al, K, Fe, and Mg), which is a composition that has been documented in association with Ediacaran fossil preservation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".