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Record W2593779614 · doi:10.1130/abs/2016am-283604

RELATING EDIACARAN FRONDS

2016· article· en· W2593779614 on OpenAlexafffund
T. Alexander Dececchi, Guy M. Narbonne, Marc Laflamme, Carolyn Greentree

Bibliographic record

VenueAbstracts with programs - Geological Society of America · 2016
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsQueen's UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFrondComputer scienceGeologyAstrobiologyPaleontologyPhysics

Abstract

fetched live from OpenAlex

Ediacaran fronds are key components of terminal-Proterozoic ecosystems.They represent one of the most widespread and common body forms ranging across all major Ediacaran fossil localities and time slices postdating the Gaskiers glaciation, but uncertainty over their phylogenetic affinities has led to uncertainty over issues of homology and functional morphology between and within organisms displaying this ecomorphology.Here we present the first large-scale, multigroup cladistic analysis of Ediacaran organisms, sampling 20 ingroup taxa with previously asserted affinities to the Arboreomorpha, Erniettomorpha, and Rangeomorpha.Using a newly derived morphological character matrix that incorporates multiple axes of potential phylogenetically informative data, including architectural, developmental, and structural qualities, we seek to illuminate the evolutionary history of these organisms.We find strong support for existing classification schema and devise apomorphy-based definitions for each of the three frondose clades examined here.Through a rigorous cladistic framework it is possible to discern the pattern of evolution within and between these clades, including the identification of homoplasies and functional constraints.This work both validates earlier studies of Ediacaran groups and accentuates instances in which previous assumptions of their natural history are uninformative.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score0.447

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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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 designOther design
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
Published2016
Admission routes2
Has abstractyes

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