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Record W4404719862 · doi:10.3390/fire7120434

Research on Wildfire and Soil Water: A Bibliometric Analysis from 1990 to 2023

2024· article· en· W4404719862 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFire · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

In the context of climate change, wildfires occur more frequently and significantly impact the vegetation–soil–water continuum. Soil water is a critical factor for understanding wildfire occurrence and predicting wildfire hazards. However, there is a lack of specific bibliometric analysis of the research on the mechanisms by which soil water influences wildfire occurrence. Therefore, this study conducted a bibliometric analysis of wildfire and soil water, aiming to understand their relationship, research characteristics, and future development trends. We used the Bibliometrix software package in R 4.4.0, which provides different methods for analyzing bibliometric data. A total of 1585 publications were analyzed from 1990 to 2023. The results of the study showed that the number of publications showed an overall growth trend during the period, with an average annual increase rate of 4.4%. The average annual citations per paper exhibited a pattern of rapid increase, followed by slow growth, and then rapid decrease. Ten highly productive authors in the field contributed 12.2% of the total publications during this period. Over the past 30 years, the University of Aveiro has consistently ranked first in terms of paper quantity. Most of the top ten productive institutions are in the United States, Australia, and several European countries. Fifty-eight countries engage in research related to wildfires and soil water, with close collaboration observed between the United States, Canada, and Spain. The four most frequently used keywords are “wildfire”, “fire”, “water repellency”, and “runoff” (with a total frequency of 1385). Water properties relevant to soil characteristics in the word cloud primarily include hydrophobicity, runoff, erosion, and infiltration. Erosion, wildfires, and runoff are crucial in the field but have yet to receive substantial development. The correlation of post-wildfire soil water properties with infiltration, runoff, and erosion processes is most likely to be addressed in future research. The findings will help researchers assess the post-wildfire disaster chain and its impact on the ecological environment, with clear trends, gaps, and research directions in the areas.

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.

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 categoriesBibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0140.102
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.015

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 head0.025
GPT teacher head0.305
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