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Record W3137342538 · doi:10.1017/s155192952100047x

3D Non-Destructive Identification of Fossil Fish from the Late Cretaceous of Alberta, Canada using Synchrotron Micro Computed Tomography

2021· article· en· W3137342538 on OpenAlexaffabout
Donald B. Brinkman, Lisa L. Van Loon, Neil R. Banerjee

Bibliographic record

VenueMicroscopy Today · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsWestern UniversityRoyal Tyrrell Museum
Fundersnot available
KeywordsFish <Actinopterygii>CretaceousIdentification (biology)Computed tomographySynchrotronGeologyPaleontologyFisheryBiologyRadiologyMedicinePhysicsEcologyNuclear physics

Abstract

fetched live from OpenAlex

The Royal Tyrrell Museum in Alberta, Canada is focused on reconstructing the communities that existed at the end of the Cretaceous. This challenge is made more difficult because for many of the taxa present, few complete specimens are preserved. In most smaller animals, all that remains preserved are isolated elements such as jaws. Teleost fish are of particular interest because they are dominant in today's aquatic communities. They are thought to have diversified after the Cretacious-Paleogene (K-Pg) mass extinction event, but many questions about early freshwater members of this group remain. Even the number of species present remains a mystery. Through an ambitious SR-μCT study we are non-destructively digitally dissecting both isolated elements and articulated skeletons that remain embedded in their rock matrix. Through comparison studies we are identifying features to aid in their identification while preserving the original fossils in an unaltered state for future studies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.212
Teacher spread0.205 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

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