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Record W2407950059 · doi:10.1017/eac.2016.4

VARIETIES OF TEXTUAL VARIANTS: EVIDENCE FROM THE TSINGHUA BAMBOO-STRIP *<i>MING XUN</i> MANUSCRIPT

2016· article· en· W2407950059 on OpenAlexaff
Edward L. Shaughnessy

Bibliographic record

VenueEarly China · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsShaughnessy Hospital
Fundersnot available
KeywordsCopyingVariation (astronomy)Similarity (geometry)Natural language processingBambooHistoryLinguisticsLiteratureComputer scienceArtArtificial intelligencePhilosophyGeneticsBiologyPhysicsBotany

Abstract

fetched live from OpenAlex

Abstract *Ming xun 命訓 is a text included among the Tsinghua University corpus of Warring States manuscripts and corresponds with a chapter by the same title in the Yi Zhou shu 逸周書. Although the manuscript and received text are quite similar, nevertheless there are numerous textual variants between them. This study provides examples of these variants, divided into five different categories: mis-writing or mis-copying; classifier variation; phonetic loans; graphic similarity; added or deleted text, as well as a sixth type of variant that might be termed “identical variants.” The study also provides complete translations of both the manuscript and received text.

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)0.002
metaresearch head score (Gemma)0.011
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0030.004
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.039
GPT teacher head0.265
Teacher spread0.226 · 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
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

Citations3
Published2016
Admission routes1
Has abstractyes

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