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Record W4411969588 · doi:10.3389/feart.2025.1609184

Research dynamics and frontier trends of orogenic gold deposits: a knowledge map based on bibliometrics

2025· article· en· W4411969588 on OpenAlexaboutno aff
Kexin Liu, Nan Jiang, Yongqiang Zhang

Bibliographic record

VenueFrontiers in Earth Science · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsBibliometricsFrontierDynamics (music)Economic geographyRegional scienceGeologyEarth scienceGeographyComputer scienceData miningArchaeologySociology

Abstract

fetched live from OpenAlex

Orogenic gold deposits represent a vital component of global gold reserves, functioning as both significant sources of gold and essential indicators for understanding crustal metallogeny within collisional tectonic environments. This study employs bibliometric analysis on 2,476 publications sourced from the Web of Science Core Collection (1995–2025) to delineate the intellectual evolution and emerging frontiers in orogenic gold research. Through systematic examination utilizing Citespace and Vosviewer, we identify publication trends, geographic distribution, institutional contributions, and citation networks of global orogenic gold deposit studies. Key findings reveal concentrated research output from China (1,031 papers), Australia (626 papers), and Canada (326 papers), with the China University of Geosciences and the University of Western Australia emerging as prominent institutional hubs. While Deng Jun and Santosh M. lead contemporary productivity metrics, foundational contributions by Groves DI (3,459 citations) and Goldfarb RJ (4,590 citations) continue to serve as pivotal citation anchors. Based on the analysis, the research frontiers should focus on three key areas: (1) Cross-scale mineralization mechanism studies, including numerical simulations of supercritical fluid (H2O-CO2 ± CH4) phase behavior, four-dimensional visualization reconstruction of lithospheric material cycles, and quantitative analysis of pressure-driven (∼150 MPa) phase transitions and adsorption kinetics in sulfide-mantle fluid coupling mechanisms; (2) Technological and methodological advancements, emphasizing the development of AI-powered three-dimensional orebody prediction models and the establishment of deep exploration technology consortia capable of penetrating up to 8 km; (3) Theoretical paradigm shifts, promoting the integration of micro-area isotopic tracing techniques with deep dynamic models to elucidate the control mechanisms of supercontinent cycles on the spatiotemporal architecture of mineralization systems. This field is transitioning from empirical exploration toward a theory-driven research paradigm.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.1070.126
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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