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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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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