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Record W2549019801 · doi:10.1144/sp448.11

X-ray microtomography as a tool for investigating the petrological context of Precambrian cellular remains

2016· article· en· W2549019801 on OpenAlexaboutno aff
Keyron Hickman‐Lewis, Russell J. Garwood, Philip J. Withers, David Wacey

Bibliographic record

VenueGeological Society London Special Publications · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research Council
KeywordsPrecambrianContext (archaeology)X-ray microtomographyGeologyEvolutionary biologyEarth sciencePaleontologyBiologyPhysicsOptics

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.028
GPT teacher head0.250
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2016
Admission routes1
Has abstractyes

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