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Record W1852254854 · doi:10.1021/ed500714f

Wildfires in the Lab: Simple Experiment and Models for the Exploration of Excitable Dynamics

2015· article· en· W1852254854 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

VenueJournal of Chemical Education · 2015
Typearticle
Languageen
FieldEngineering
TopicSlime Mold and Myxomycetes Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSimple (philosophy)GRASPFirefightingProperty (philosophy)Dynamics (music)Computer scienceWork (physics)Lead (geology)Scale (ratio)Biochemical engineeringEnvironmental scienceEngineeringChemistryGeographyGeologyEpistemologyMechanical engineeringSociology

Abstract

fetched live from OpenAlex

Wildfires lead to the loss of life and property in many parts of the world. Understanding their dangers and, more particularly, the underlying dynamics which lead to fires of catastrophic scale contributes to better awareness as well as prevention and firefighting capabilities within the affected areas. In order to enable a basic understanding of the mechanisms of fire propagation for high school and college students, we present here simple model experiments using match sticks that demonstrate the dangers of spatial coupling between individual reactive (combustible) elements leading to rapid spreading of the combustion reaction. Supplemented with easy-to-grasp numerical simulations, our work illustrates the dynamics of wildfires in impressive but controllable ways and puts wildfire propagation into the fascinating framework of excitable active media which have many equivalents in chemical, ecological, biological or societal systems.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.086

Codex and Gemma teacher scores by category

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

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 head0.062
GPT teacher head0.332
Teacher spread0.270 · 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