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Record W4401786548 · doi:10.1111/pala.12721

Priapulid neoichnology, ecosystem engineering, and the Ediacaran–Cambrian transition

2024· article· en· W4401786548 on OpenAlexaff
Katherine A. Turk, Achim Wehrmann, Marc Laflamme, Simon A.F. Darroch

Bibliographic record

VenuePalaeontology · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsUniversity of Toronto
FundersNatural Environment Research CouncilDeutscher Akademischer AustauschdienstUS-UK Fulbright CommissionSight Research UKAssociation for Women GeoscientistsU.S. Department of StateNational Science FoundationPaleontological SocietyFulbright U.S. Student Program
KeywordsPaleontologyEcosystemGeologyTransition (genetics)EcologyBiologyGenetics

Abstract

fetched live from OpenAlex

Abstract The evolutionary rise of powerful new ecosystem engineering impacts is thought to have played an important role in driving waves of biospheric change across the Ediacaran–Cambrian transition (ECT; c . 574–538 Ma). Among the most heavily cited of these is bioturbation (organism‐driven sediment disturbance) as these activities have been shown to have critical downstream geobiological impacts. In this regard priapulid worms are crucial; trace fossils thought to have been left by priapulan‐grade animals are now recognized as appearing shortly before the base of the Cambrian and represent some of the earliest examples of bed‐penetrative bioturbation. Understanding the ecosystem engineering impacts of priapulids may thus be key to reconstructing drivers of the ECT. However, priapulids are rare in modern benthic ecosystems, and thus comparatively little is known about the behaviours and impacts associated with their burrowing. Here, we present the early results of neoichnological experiments focused on understanding the ecosystem engineering impacts of priapulid worms. We observe for the first time a variety of new burrowing behaviours (including the formation of linked burrow networks and long in‐burrow residence times) hinting at larger ecosystem engineering impacts in this group than previously thought. Finally, we identify means by which these results may contribute to our understanding of tracemakers across the ECT, and the role they may have had in shaping the latest Ediacaran and earliest Cambrian biosphere.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.740

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 head0.005
GPT teacher head0.186
Teacher spread0.181 · 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

Citations17
Published2024
Admission routes1
Has abstractyes

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