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Record W2273778048

Physical phenomena governing the behaviour of wildfires : numerical
\n simulation of crown fires in boreal fores

2011· preprint· en· W2273778048 on OpenAlexaboutno aff
Dominique Morvan, K.A. Gavrilov, Dmitry V. Lyubimov

Bibliographic record

VenueDSpace (Centre National De La Recherche Scientifique) · 2011
Typepreprint
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsTaigaBorealVegetation (pathology)Atmosphere (unit)MeteorologyEnvironmental scienceCrown (dentistry)Front (military)ClimatologyAtmospheric modelAtmospheric sciencesPhysical geographyGeologyGeographyForestryMaterials science
DOInot available

Abstract

fetched live from OpenAlex

This paper presents the physical phenomena
\n contributing to the behaviour of wildfires. The problem was formulated using a
\n multiphase approach, including the set of balance equations governing the coupled system
\n formed by the vegetation and the surrounding atmosphere in the vicinity of the fire
\n front. Some numerical simulations carried out for a crown fire in boreal forest are
\n compared to data collected during an experimental campaign conducted in the North West
\n territories in Canada.

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 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)0.003
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 score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.065
GPT teacher head0.322
Teacher spread0.257 · 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 teacher head, not a consensus.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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