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Record W2706270239 · doi:10.1002/ca.22942

One vowel or two? Diphthongs, digraphs, ligatures, and diaereses, oh my!

2017· article· en· W2706270239 on OpenAlexaff
Paul E. Neumann

Bibliographic record

VenueClinical Anatomy · 2017
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsDalhousie University
Fundersnot available
KeywordsDiphthongSpellingPronunciationOrthographyVowelLinguisticsPhonologyMedicineFocus (optics)Philosophy

Abstract

fetched live from OpenAlex

This is the first in a short series about orthography in anatomical Latin. Although phonology is an important aspect of diphthongs and digraphs, the focus here is on spelling, not the more complicated topic of pronunciation. Recommendations are made for standard spellings of words that contain or may appear to contain diphthongs in Latin anatomical words or their ancient Greek sources. Ligatures and diaereses (typographical symbols that were developed after the classical period) are not recommended for use in anatomical Latin terms. Clin. Anat. 30:1013-1016, 2017. © 2017 Wiley Periodicals, Inc.

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)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.012

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 head0.136
GPT teacher head0.454
Teacher spread0.318 · 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
GenreOther

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

Citations6
Published2017
Admission routes1
Has abstractyes

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