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Record W2168589269 · doi:10.1139/x02-176

Airtanker initial attack: a spreadsheet-based modeling procedure

2003· article· en· W2168589269 on OpenAlexvenueno aff
Francis E. Greulich

Bibliographic record

VenueCanadian Journal of Forest Research · 2003
Typearticle
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceFlexibility (engineering)Base (topology)Point (geometry)Distribution (mathematics)SimulationStatisticsMathematicsGeometry

Abstract

fetched live from OpenAlex

Airtankers are widely employed in wildland fire control operations. This paper presents a spreadsheet procedure for modeling airtanker initial-attack performance within a protection region. Easily written and modified, this spreadsheet-based model provides the user with substantial flexibility when specifying the spatial distribution of fire occurrence within the initial-attack zone of an airtanker base. Once this spatial distribution has been specified, the expected flight distance from the airtanker base to a random fire ignition point as well as higher moments of the flight distance distribution are readily computed and applied using the spreadsheet. The chief advantages of this spreadsheet approach are described. Calculation procedures and potential applications of flight distance moments including the optimization of airbase location are illustrated. Detailed numerical examples and opportunities for future development are indicated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.005

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 head0.057
GPT teacher head0.323
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations12
Published2003
Admission routes1
Has abstractyes

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