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New insights into the Precambrian fossil record using correlative electron and ion beam microscopy

2016· other· en· W4235871101 on OpenAlexaboutno aff
David Wacey, Kate Eiloart, Martin Saunders, Paul Guagliardo, Matt R. Kilburn

Bibliographic record

VenueEuropean Microscopy Congress 2016: Proceedings · 2016
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsFocused ion beamPrecambrianFossil RecordNanotechnologySecondary ion mass spectrometryPaleontologyGeologyChemistryMaterials scienceIon

Abstract

fetched live from OpenAlex

Earth's rock record holds great potential for decoding the origin and early diversification of life on our planet. However, the interpretation of the Precambrian (older than ~541 million years ago) fossil record is fraught with difficulties. These include: the fragmentary nature of the sedimentary rock record with large periods of time unrepresented and certain habitats under‐represented; and the nature of the organisms, being microscopic, morphologically simple and often only subtly different from co‐occurring non‐biological organic material. Distinguishing between true signs of life and abiotic artefacts requires analytical techniques with excellent spatial resolution in two and three dimensions, in order to accurately analyse key features of putative cells such as cell wall ultrastructure, biochemistry, and interaction of cell walls with the minerals that have fossilised them [1]. Likewise, distinguishing different grades of life (for example, simple prokaryotes versus more complex eukaryotes) requires similar techniques, in order to identify putative multi‐cellularity and specific types of cell contents and cell wall architecture. We here demonstrate how a protocol combining focused ion beam (FIB) milling, SEM, TEM and nano‐scale secondary ion mass spectrometry (SIMS) can reveal unprecedented nanometer to micrometer scale details of Precambrian fossilised organisms, providing more robust biosignatures for both prokaryotes and eukaryotes for future studies on Earth or other planets. FIB milling was used to prepare ultrathin (c. 100 nm) wafers from standard geological thin sections for TEM analysis, plus slightly thicker wafers (c. 150‐200 nm) that could be used for both TEM and NanoSIMS analysis. The latter meant that both TEM and NanoSIMS data could be collected from a single candidate microfossil: TEM data included ChemiSTEM elemental mapping of major elements, STEM‐EELS analysis of the bonding and structure of organic material, and electron diffraction to identify mineral phases; NanoSIMS data included targeted analysis of trace elements in organic material (e.g., N, S, P) and in the fossilising mineral phases. Analysis of FIB‐milled wafers counteracts the problems previously associated with surface analysis techniques such as NanoSIMS (i.e. surface contamination and polishing effects). FIB‐milling was also combined with SEM imaging (3D slice and view) in order to obtain accurate 3D visualisations of candidate microfossils. Data will be presented from three geological formations that play an important role in our understanding of the origin and evolution of early life on Earth: 1, The 1878 Ma Gunflint Formation of Canada, containing an iconic suite of diverse microfossils used as a benchmark for high quality preservation of early life in marine environments [2]; 2, The 1000 Ma Torridon Group of northwest Scotland (Fig. 1) that is renowned for exceptional three‐dimensional preservation of both prokaryotes and eukaryotes in phosphate and clay minerals in a terrestrial (lake) setting [3]; 3, The 850 Ma Bitter Springs Formation of central Australia that shows exquisite microfossil preservation (including putative cell contents) in micro‐quartz [4].

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.245
Teacher spread0.235 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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