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Record W4296702469 · doi:10.1098/rsos.220773

Acorn worm ossicle ultrastructure and composition and the origin of the echinoderm skeleton

2022· article· en· W4296702469 on OpenAlexafffund
Charles Larouche‐Bilodeau, Christopher B. Cameron

Bibliographic record

VenueRoyal Society Open Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEchinoderm biology and ecology
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOssiclesOssicleEchinodermBiologyAnatomyCalciteOtolithBiomineralizationEcologyPaleontologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Here, we describe the shape and mineral composition of ossicles from eight acorn worm species, bringing the total known biomineralizing enteropneusts to 10 and confirming that ossicles are widespread in Enteropneusta. Three general forms were identified including a globular form that occurs in all three major enteropneust families. The biomineral compositions included all three polymorphs of calcium carbonate; calcite, aragonite and vaterite, and low to high magnesium concentrations. Calcite was the most common and characteristic of echinoderm ossicles. Based on these findings we hypothesize that an enteropneust-like ancestor to the Ambulacraria had ectodermal ossicles, formed in an extracellular occluded space bordered by a sheath of sclerocyte cells. The ossicles were microscopic, monotypic globular shaped, calcite ossicles with low to high Mg content and MSP130 proteins. The ossicles lacked intercalation with other ossicles. The function of acorn worm ossicles is unknown, but the position of ossicles in the trunk epithelia and near to the surface suggests predator deterrence, to provide grip on the walls of a burrow or tube, as storage of metabolic waste, or to regulate blood pH, rather than as an endoskeleton function seen in fossil and crown group Echinodermata.

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)0.001
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 score0.265
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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

Citations8
Published2022
Admission routes2
Has abstractyes

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