X-ray microtomography as a tool for investigating the petrological context of Precambrian cellular remains
Bibliographic record
Abstract
Abstract A wide spectrum of tomographic techniques now exists for studying palaeontological specimens, but the suitability of these methods for assessing Earth's oldest prokaryotic life has not been comprehensively investigated. We evaluated the ability of X-ray computed tomography – specifically X-ray microtomography – to reveal the morphology and petrological context of Precambrian microfossils, pseudofossils and biosedimentary structures, all of which are important in the origin and early evolution of life of Earth. The materials tested came from the Pilbara Craton of Western Australia (the 3.49 Ga Dresser Formation, the 3.46 Ga Apex chert and the 3.43 Ga Strelley Pool Formation) and the 1.88 Ga Gunflint Formation of Ontario, Canada. These units chart key developments in palaeobiology. The oldest formations contain profoundly controversial microfossil-like objects and microbially-induced sedimentary structures, whereas definitive prokaryotes are found in the youngest formations. We demonstrate that the imaging of individual microfossils and pseudofossils currently lies at the limits of the capabilities of laboratory-based X-ray microtomography and requires beneficial taphonomy. However, microtomography does provide a good overview of their petrological context at flexible spatial scales, although the quality of the data obtained from mesoscopic microbially-induced sedimentary structures and stromatolites depends largely on their style of preservation. Supplementary material: A zipped Drishti volume for all CT scans, a 0.7z split zip file of one Drishti volume and a HDMI supplementary movie showing digital visualizations for all of the scans are available at https://doi.org/10.5281/zenodo.58161
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".