MétaCan
Menu
Back to cohort
Record W1737188869

An Examination on the Historical Distribution and Transformation of Cinnabar Localities Through Chinese Materia Medica Works

2015· article· en· W1737188869 on OpenAlexvenueno aff
Shiyuan Wang

Bibliographic record

VenueCross-cultural communication · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMetallurgy and Cultural Artifacts
Canadian institutionsnot available
Fundersnot available
KeywordsCinnabarMateria medicaGeographyChinaAncient historyHistoryArchaeologyGeologyMineralogyMedicine
DOInot available

Abstract

fetched live from OpenAlex

The distribution and transformation of cinnabar localities in the history of China as reflected in Chinese materia medica works has been a dynamic process. In the Pre-Qin Period and Qin-Han Dynasties, mining clustered around the few cinnabar localities that were scattered. During Wei, Jin, and the Southern and Northern Dynasties, the number of cinnabar localities gradually increased, and there was a shift of production center. In Tang-Song Dynasties, localities containing cinnabar were more explicitly identified and significantly expanded in size; the tendency toward a shift of production center became more obvious. During Yuan, Ming, and Qing Dynasties, the size of cinnabar localities continued to expand a little. The increasing expansion of the localities and the gradual shift of production center was the result of the interplay of many factors including the medicinal attributes and functions of cinnabar, society’s demand for cinnabar, mining technologies, the attributes of cinnabar as a natural resource and its religious and cultural functions. An in-depth examination and understanding of the pattern of distribution and transformation of cinnabar localities through Chinese materia medica works would offer better guidance for present-day mining of cinnabar and selection of authentic herbal medicine.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.002
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 head0.059
GPT teacher head0.358
Teacher spread0.299 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCross-cultural communicationSame topicMetallurgy and Cultural ArtifactsFrench-language works237,207