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Record W4366551218 · doi:10.5376/ijh.2023.13.0005

Tracing and Etymological Study on Peony and Mudan

2023· article· en· W4366551218 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Horticulture · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicZiziphus Jujuba Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsEtymologyCivilizationHistoryChinaPeriod (music)Ancient historyVariety (cybernetics)History of ChinaClassicsLiteratureArtArchaeology

Abstract

fetched live from OpenAlex

Peony and Mudan both originated in China. Mudan came after peony, which has been recognized by the academic community and internationally. However, where did peony and Mudan come from and where did they distribute, and what are the similarities and differences between them? There has always been controversy, and there is also a lack of historical documents to support it. This study attempts to clarify and study previous existence of Peony and Mudan and their relationship with Chinese civilization from the perspective of natural history and etymology. This study shows that peony was widely planted or picked in the Spring and Autumn Period 2400 years ago; 2000 years ago in the Han Dynasty, Mudan had been differentiated from peony and evolved into an independent variety. 1400 years ago in the Tang Dynasty, Peony and Mudan were clearly distinguished, especially in the middle and late Tang Dynasty (7th century AD).

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.

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 score0.572
Threshold uncertainty score0.088

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 head0.026
GPT teacher head0.285
Teacher spread0.259 · 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