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Record W2055283372 · doi:10.1002/dvdy.20718

Skeletal elements in the vertebrate eye and adnexa: Morphological and developmental perspectives

2006· review· en· W2055283372 on OpenAlexafffund
Tamara A. Franz‐Odendaal, Matthew K. Vickaryous

Bibliographic record

VenueDevelopmental Dynamics · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyVertebrateAnatomyOssiclesSkeleton (computer programming)Eye developmentNeural crestAxial skeletonCartilageEvolutionary biologyCell biologyTranscription factorGeneticsMiddle earEmbryo

Abstract

fetched live from OpenAlex

Although poorly appreciated, the vertebrate eye and adnexa are relatively common sites for skeletogenesis. In many taxa, the skeleton contributes to internal reinforcement in addition to the external housing of the eye (e.g., the circumorbital bones and eyelids). Eyeball elements such as scleral cartilage and scleral ossicles are present within a broad diversity of vertebrates, albeit not therian mammals, and have been used as important models for the study of condensations and epithelial-mesenchymal interactions. In contrast, other elements invested within the eye or its close surroundings remain largely unexplored. The onset and mode of development of these skeletal elements are often variable (early versus late; involving chondrogenesis, osteogenesis, or both), and most (if not all) of these elements appear to share a common neural crest origin. This review discusses the development and distribution of the skeletal elements within and associated with the developing eye and comments on homology of the elements where these are questionable.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.013
GPT teacher head0.277
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 designNot applicable
Domainnot available
GenreReview

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

Citations75
Published2006
Admission routes2
Has abstractyes

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