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Record W4412356215 · doi:10.1080/19376812.2025.2530636

Footprints of drought in a montane grassland biome: a drought vulnerability index approach to drought conditions

2025· article· en· W4412356215 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAfrican Geographical Review · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Drought Analysis
Canadian institutionsYork University
Fundersnot available
KeywordsBiomeGrasslandVulnerability (computing)Montane ecologyIndex (typography)Drought toleranceDrought resistanceEnvironmental scienceClimatologyGeographyEcologyAgronomyEcosystemBiologyGeology

Abstract

fetched live from OpenAlex

This study examines the impact of drought episodes during the summer and spring months on the socio-ecological livelihoods within the Maloti-Golden Gate Highlands. Given the increasing frequency and intensity of droughts worldwide, montane environments such as the Maloti remain under-researched despite their ecological significance. This study addresses this gap by utilizing MODIS-derived Vegetation Condition Index (VCI) retrieved from AppEEARS, specifically MOD13Q1 (2001–2020), alongside socioeconomic data obtained from Statistics South Africa (SSA) to assess drought vulnerability at a fine spatial scale. The results indicate a decreasing trend in precipitation over time, with 2015 being the driest year. Phuthaditjhaba was recognized as the most vulnerable region, closely followed by Kestell, due to demographic and economic factors. This study highlights the urgent need for localized drought mitigation strategies that consider environmental and socioeconomic components.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.008
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.272
Teacher spread0.262 · 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