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Record W3176962166 · doi:10.1038/s41598-020-72648-6

Molecular tests support the viability of rare earth elements as proxies for fossil biomolecule preservation

2020· article· en· W3176962166 on OpenAlexfundno aff
Paul V. Ullmann, Kristyn K. Voegele, David E. Grandstaff, R. D. Ash, Wenxia Zheng, Elena R. Schroeter, Mary H. Schweitzer, Kenneth J. Lacovara

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsnot available
FundersRowan UniversityJurassic FoundationConcordia University of EdmontonNational Science Foundation
KeywordsDiagenesisTaphonomyRare-earth elementGeologyCretaceousPaleontologyRare earthChemistryBiologyMineralogy

Abstract

fetched live from OpenAlex

The rare earth element (REE) composition of a fossil bone reflects its chemical alteration during diagenesis. Consequently, fossils presenting low REE concentrations and/or REE profiles indicative of simple diffusion, signifying minimal alteration, have been proposed as ideal candidates for paleomolecular investigation. We directly tested this prediction by conducting multiple biomolecular assays on a well-preserved fibula of the dinosaur Edmontosaurus from the Cretaceous Hell Creek Formation previously found to exhibit low REE concentrations and steeply-declining REE profiles. Gel electrophoresis identified the presence of organic material in this specimen, and subsequent immunofluorescence and enzyme-linked immunosorbant assays identified preservation of epitopes of the structural protein collagen I. Our results thereby support the utility of REE profiles as proxies for soft tissue and biomolecular preservation in fossil bones. Based on considerations of trace element taphonomy, we also draw predictions as to the biomolecular recovery potential of additional REE profile types exhibited by fossil bones.

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)0.003
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.022
GPT teacher head0.250
Teacher spread0.228 · 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".

Quick stats

Citations19
Published2020
Admission routes1
Has abstractyes

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Same venueScientific ReportsSame topicPaleontology and Evolutionary BiologyFrench-language works237,207