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Record W4408331772 · doi:10.1017/pab.2024.55

Growth of the enigmatic Ediacaran <i>Parvancorina minchami</i>

2025· article· en· W4408331772 on OpenAlexaff
A. Yu. Ivantsov, Andrew H. Knoll, Maria Zakrevskaya, M. A. Fedonkin, Daniel Pauly

Bibliographic record

VenuePaleobiology · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTrilobiteLongevityOrdovicianInvertebratePaleontologyMarine invertebratesBiologyEcologySiliciclasticGeologyStructural basin

Abstract

fetched live from OpenAlex

Abstract Analysis of length-frequency data using the ELEFAN (Electronic Length-Frequency Analysis) approach and software is widely used to quantify the growth, mortality, longevity, and related parameters of Recent marine animals. Here we analyze a sample ( n = 211) of the Ediacaran metazoan Parvancorina minchami Glaessner, 1958, from the Vendian siliciclastic marine deposits of the southeastern White Sea region, Russia. The results fit a von Bertalanffy equation with the parameters L ∞ = 2 cm, K = yr −1 (with t 0 not estimated) and an instantaneous rate of mortality ( M ) of 1.44 yr −1 , implying M / K ≈ 2, as commonly occurs in Recent small invertebrates. These parameter values also imply a longevity for P. minchami of about 4 yr. The concepts and approach used here, previously applied to an Ordovician trilobite and a Cambrian radiodont, suggest that inferences on growth, mortality, longevity, and related parameters can be obtained from suitable size-frequency samples of long-extinct metazoans, opening new vistas on their growth dynamics and functional roles in ancient ecosystems.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.247

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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