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Record W7023895808

Preservation of Neuropteris ovata in roof shale and in fluvial crevasse-splay facies (Late Pennsylvanian, Sydney Coalfield, Canada): Part I: An infrared-based chemometric model

2020· article· en· W7023895808 on OpenAlexaboutno aff

Bibliographic record

VenueConicet · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsFaciesOil shaleFluvialCarboniferousReticulateTaphonomyPaleozoicClastic rock
DOInot available

Abstract

fetched live from OpenAlex

Analytical questions relating to the influence of sedimentation on the preservation states of Carboniferous plant fossils are seldom addressed in the literature. Here we address specifically the influence facies differences have on preservation states and suggest how they can be analyzed. The case study involves the seed fern Neuropteris ovata (Hoffmann) that occurs as opaque pinnules in the roof shale and as transparent pinnules in an associated crevassesplay of the basal Cantabrian in age, Point Aconi Coal Seam, Sydney Coalfield, Canada. The color differences imply different molecular pathways for organic matter transformation over geological time, which resulted in production of compression fossils in the roof shale and fossilized-cuticle in the crevasse-splay, respectively. Fourier transform infrared spectroscopy methods are used to quantify functional groups, and the derived data are chemometrically evaluated. Results indicate that the compressions are, as anticipated, characterized in the crevasse-splay facies by a predominantly aromatic composition. The fossilized-cuticles, however, are mainly characterized by oxygen-containing aliphatics, confirming the influence of facies changes on preservation states of the species studied. Implications for preservation, taxonomy, and paleoecology are emphasized.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.749

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.220
Teacher spread0.179 · 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 designSimulation or modeling
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

Citations0
Published2020
Admission routes1
Has abstractyes

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