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Record W2035324985 · doi:10.1666/10012.1

Classifying echinoid skeleton models: testing ideas about growth and form

2011· article· en· W2035324985 on OpenAlexafffund
Maria Abou Chakra, Jon R. Stone

Bibliographic record

VenuePaleobiology · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCladogramSkeleton (computer programming)Morphology (biology)PaleontologyField (mathematics)AnalogyFossil RecordTaphonomyGeologyBiologyCladisticsPhylogenetic treeEpistemologyPhilosophyAnatomyMathematicsPure mathematics

Abstract

fetched live from OpenAlex

Theoretical morphology is the scientific field in which researchers model organism growth and form. The field is developed well in studies on skeletons, especially shells. Researchers have contributed echinoid skeleton models to the field, but these have yet to be recognized collectively. We present herein the first comprehensive review for echinoid skeleton models in theoretical morphology. We apply a phylogenetic systematic analysis to those models, use the resulting consensus cladogram to classify and interrelate the models in an analogy in which they are likened to fossil specimens in a biostratigraphic record, and utilize the biostratigraphic metaphor to define trends within theoretical morphology as it applies to echinoid skeleton models.

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 score0.312
Threshold uncertainty score0.534

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 head0.062
GPT teacher head0.221
Teacher spread0.159 · 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

Citations15
Published2011
Admission routes2
Has abstractyes

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