MétaCan
Menu
Back to cohort
Record W4288144163 · doi:10.6084/m9

Can trophic rewilding reduce the impact of fire in a more flammable world?

2014· preprint· en· W4288144163 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

VenueUTAS Research Repository · 2014
Typepreprint
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsUniversity of Windsor
FundersFundação de Amparo à Ciência e Tecnologia do Estado de PernambucoPolska Akademia NaukCentre National de la Recherche ScientifiqueConselho Nacional de Desenvolvimento Científico e TecnológicoConsejo Nacional de Investigaciones Científicas y TécnicasAgence Nationale de la Recherche
KeywordsDynamics (music)Evolutionary dynamicsSociologyData scienceCognitive scienceComputer sciencePsychology

Abstract

fetched live from OpenAlex

Large vertebrates affect fire regimes in several ways: by consuming plant matter that would otherwise accumulate as fuel; by controlling and varying the density of vegetation; and by engineering the soil and litter layer. These processes can regulate the frequency, intensity and extent of fire. The evidence for these effects is strongest in environments with intermediate rainfall, warm temperatures and graminoid-dominated ground vegetation. Probably, extinction of Quaternary megafauna triggered increased biomass burning in many such environments. Recent and continuing declines of large vertebrates are likely to be significant contributors to changes in fire regimes and vegetation that are currently being experienced in many parts of the world. To date, rewilding projects that aim to restore large herbivores have paid little attention to the value of large animals in moderating fire regimes. Rewilding potentially offers a powerful tool for managing the risks of wildfire and its impacts on natural and human values.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.098
GPT teacher head0.455
Teacher spread0.358 · 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