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Record W1864587562 · doi:10.3968/7341

Analysis of Journal Papers about Studies of Ancient Chinese Villages

2015· article· en· W1864587562 on OpenAlexvenueno aff
Long Liu

Bibliographic record

VenueCanadian social science · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicKorean Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChinaSettlement (finance)GeographySpace (punctuation)History of ChinaDistribution (mathematics)HistoryArchaeologyAncient historyComputer science

Abstract

fetched live from OpenAlex

Based on CNKI database, the author has retrieved that, from 1989 to 2015, 318 papers about ancient village studies have been published in core Chinese journals. With literature statistical methods, the author analyzes and classifies the year and the number of studies, research themes, journals in which the papers are published, main creative units of such literature, core author group distribution and teases out there are 318 first authors and 12 main core authors as well as 11 core journals. The results show that ancient Chinese village landscape construction, ancient town settlement space type, traditional residential building space, village cultural landscape protection and sustainable development, reproduction of space environment of ancient villages, ancient village landscape planning, protection and development of ancient villages, the development and protection of the ancient village landscape are the hot spots in ancient villages researches in China and have made great achievements and progress.

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)0.006
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0980.136
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0110.002

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 head0.024
GPT teacher head0.281
Teacher spread0.257 · 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.

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
Published2015
Admission routes1
Has abstractyes

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