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Record W3199933884 · doi:10.1155/2021/9274918

Changes in the Structures and Directions of Rock Excavation Research from 1999 to 2020: A Bibliometric Study

2021· article· en· W3199933884 on OpenAlexaboutno aff
Dongping Shi, Chengyu Xie, Lichun Xiong

Bibliographic record

VenueAdvances in Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsnot available
FundersNatural Science Foundation of Hunan ProvinceEducation Department of Hunan Province
KeywordsExcavationMining engineeringGeologyArchaeologyForensic engineeringEngineeringGeotechnical engineeringHistory

Abstract

fetched live from OpenAlex

Rock excavation has been the hot spot and frontier of scientific research. Rock excavation research is in a period of rapid development. The bibliographies included in ISI Web of Knowledge database from 1999–2020 were used as data samples, and the collected data were analyzed by literature co‐citation and cluster analysis using CiteSpace and VOSviewer information visualization techniques and dynamic network analysis tools. A knowledge map of the evolution of bibliometric research development is drawn to reveal the representative literature in the field of bibliometrics. The hot areas of bibliometric research are introduced. The development trend of bibliometrics is proposed. The results of the study show that the amount of the literature on rock excavation is growing rapidly. A large amount of the foreign literature is available in China, the United States, Australia, Canada, France, and other countries. The main included journals are Tunnelling and Underground Space Technology, International Journal of Rock Mechanics and Mining Sciences, “Rock Mechanics and Rock Engineering,” “Engineering Geology,” and “Bulletin of Engineering Geology and the Environment.” Keyword co‐occurrence analysis includes the following contents: rock damage constitutive model, excavation damage area, numerical simulation, stability analysis support, and prediction technology of rock.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0910.177
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.302
Teacher spread0.279 · 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

Labeled directly by 2 models reading the full record.

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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in Civil EngineeringSame topicTunneling and Rock MechanicsCategoryBibliometricsFrench-language works237,207