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Record W2964436615 · doi:10.1130/abs/2019am-339519

FLUORESCENCE PROPERTIES OF EXCEPTIONALLY PRESERVED COLORED LEAVES FROM THE PLIOCENE OF THE WILLERSHAUSEN LAGERSTÄTTE, GERMANY

2019· article· en· W2964436615 on OpenAlexaff
Klaus Wolkenstein, Gernot Arp

Bibliographic record

VenueAbstracts with programs - Geological Society of America · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Ecology and Soil Science
Canadian institutionsGeoscience BC
Fundersnot available
KeywordsLagerstätteFluorescenceColoredGeologyPaleontologyAstrobiologyMaterials scienceBiologyOpticsPhysics

Abstract

fetched live from OpenAlex

The Willershausen Fossil-Lagerstätte in Germany is well-known for the exceptional preservation of plant and animal fossils and represents one of the taxonomically richest Pliocene assemblages in Europe. Vertebrate fossils found in the laminated carbonates from Willershausen often show preservation of soft parts, and leaves are famous for their color preservation. Here, we report the discovery of distinct UV-light induced fluorescence in different fossil angiosperm leaf taxa from Willershausen. An astonishing observation was the presence of different fluorescence colors that ranged from yellow to red. Moreover, fluorescence properties were found to be related to genera. Using confocal laser scanning microscopy, fluorescence emission spectra were measured from fossil and present-day leaves. On the basis of their emission maxima, it was possible to distinguish broad groups of fluorophores. Our results suggest that fluorescence properties of the Willershausen leaves are mainly caused by taxon-dependent degeneration of organic compounds during senescence. Therefore, fluorescence properties might be used for supplementary taxonomic information. Because the investigated leaf fossils from Willershausen were found in a single horizon, it can be excluded that observed differences in fluorescence properties are the result from differences in diagenesis.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.201
Teacher spread0.183 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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