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Record W2025620644 · doi:10.1666/11022.1

Macroevolutionary trends in silicoflagellate skeletal morphology: the costs and benefits of silicification

2012· article· en· W2025620644 on OpenAlexaff
Helena M. van Tol, Andrew J. Irwin, Zoe V. Finkel

Bibliographic record

VenuePaleobiology · 2012
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsMount Allison University
Fundersnot available
KeywordsCenozoicExtinction (optical mineralogy)Silicic acidBiologyEcologyMorphology (biology)Fossil RecordGrazing pressurePaleontologyGrazingGeologyOceanography

Abstract

fetched live from OpenAlex

The silicoflagellates are a class of enigmatic chrysophytes characterized by netlike skeletons composed of opaline silica. Other major groups of siliceous plankton—the diatoms and radiolarians—exhibit evidence of decreasing size or silicification over the Cenozoic. We investigated trends in the silicoflagellate fossil record by constructing a species-level database of diversity and morphological metrics. This new database reveals a proliferation of silicoflagellate species with spined skeletons along with an increase in the mean number of spines per species over the Cenozoic. Although there is little change in skeleton size or silicification among species with spines, those without spines are larger than species with spines and exhibit a decrease in size toward the present. Increased grazing pressure combined with declining surface silicate availability may have shifted the costs and benefits of silicification, causing divergent responses in skeletal morphology between these different morphological lineages of silicoflagellates over time. We postulate that diminishing Cenozoic surface silicic acid availability may have predisposed large spineless silicoflagellate species to extinction, whereas increased grazing pressure may have contributed to the extinction of all remaining spineless species within the edible size range of grazers.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.287
Teacher spread0.264 · 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

Citations26
Published2012
Admission routes1
Has abstractyes

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