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Record W4242617167 · doi:10.1017/9781139540704.033

Grammar and exercises for 5F

2018· book-chapter· en· W4242617167 on OpenAlexaff

Bibliographic record

VenueCambridge University Press eBooks · 2018
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLexicography and Language Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGrammarVocabularyReading (process)Computer scienceLinguisticsLatin AmericansArtificial intelligenceNatural language processingPhilosophy

Abstract

fetched live from OpenAlex

Reading Latin, first published in 1986, is a bestselling Latin course designed to help mature beginners read classical Latin fluently and intelligently. It does this in three ways: it encourages the reading of continuous texts from the start; it offers generous help with translation at every stage; and it integrates the learning of classical Latin with an appreciation of the influence of the Latin language upon English and European culture from antiquity to the present. The Text and Vocabulary, richly illustrated, consists at the start of carefully graded adaptations from original classical Latin texts. The adaptations are gradually phased out until unadulterated prose and verse can be read. The accompanying Grammar and Exercises volume completes the course by supplying all the grammatical help needed, and the second edition has been fully revised and updated. It has also been extensively redesigned to make it clearer and easier to navigate.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.870
Threshold uncertainty score1.000

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 studies0.0010.001
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 head0.034
GPT teacher head0.193
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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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