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Record W4390413283 · doi:10.54097/ehss.v23i.12924

Spiritual Travel in Chinese Landscapes ---- Travelers Among Mountains and Streams and Murals from Yulin Caves

2023· article· en· W4390413283 on OpenAlexaff
Ziting Liao

Bibliographic record

VenueJournal of Education Humanities and Social Sciences · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsQueen's University
Fundersnot available
KeywordsPaintingCaveTheme (computing)Landscape paintingChinaVisual artsArtContextualizationArchaeologyGeographyHistoryComputer science

Abstract

fetched live from OpenAlex

Chinese landscape painting is a non-negligible category in Chinese art history. Unfortunately, the intrinsic fragility of silk results in an obscure provenance of numerous existing silk landscape paintings from ancient Chinese art. Murals in Yulin Caves, located in the northwestern province of Gansu, China, emerge as an invaluable repository that complements these delicate silk paintings. This paper selects The Illustration of Samantabhadra from Caves 29 and 3 of Yulin Caves, both illustrations in caves were created after the Song Dynasty (960-1279 CE), to compare Travelers Among Mountains and Streams (Travelers) painted in the 10th to early 11th century by Fan Kuan (c. 950-1032). The visual comparison involves the panoramic view and the travel theme. The comparison based on the different mediums will discuss the elimination of physical constraints through painted landscapes with the contextualization of murals in situ. Natural light will also be considered as one external factor that influences the artwork viewing experiences of audiences. Comparisons involved in this paper aim to examine the underlying relationships between Song landscape paintings and the subsequent landscape murals, extend the conventional concept of travelers in Song landscape paintings by identifying mountains in murals, and explore how landscapes in silk paintings and murals encourage audiences to experience spiritual travel.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.961

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 communication0.0000.001
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 head0.055
GPT teacher head0.333
Teacher spread0.278 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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