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Record W4312935698 · doi:10.14195/978-989-26-2298-9_33

Fire Weather Warnings in Croatia

2022· book-chapter· en· W4312935698 on OpenAlex
Tomislav Kozarić, Tomislava Hojsak, Marija Mokorić

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueImprensa da Universidade de Coimbra eBooks · 2022
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceVegetation (pathology)OrographyMeteorologyLightning (connector)GeographyClimatologyPrecipitation

Abstract

fetched live from OpenAlex

Vegetation fires are among the most dangerous natural hazards. In Croatia, they are most common on the Adriatic coast and in the areas near the Adriatic, especially in summer when the peak of the fire season occurs. Meteorological risk of vegetation fires in Croatia is primarily assessed with the Canadian Forest Fire Weather Index and derived fire danger. However, due to the rare spatial and temporal availability of these data as well as the effects of climate change resulting in frequent enhanced fire danger during the summer, the need for additional risk assessment tool has emerged. In that sense, the fire weather warnings were introduced ten years ago and since then have been constantly improved and adapted to the needs of the firefighting community. The aim is to warn of weather conditions that can lead to the rapid spread and unpredictable behavior of the vegetation fires. As a basic condition, fire weather warnings are issued when the fire danger classes from the Canadian Forest Fire Weather Index are high and very high. Except the meteorological parameters of the Fire Weather Index, the most important of which is wind, the behavior and spread of vegetation fires can be further influenced by atmospheric turbulence and instability in the dry air near the ground and in the lower atmosphere. These parameters also depend on the orography of the terrain and are not included in the Fire Weather Index. Two years ago, three levels of warnings were defined, the thresholds of which depend on the values and duration of wind, turbulence and instability. In addition to the detailed explanation of the method for issuing fire weather warnings, the paper presents textual and graphical warning examples, describes five critical fire weather patterns when conditions for issuing warning are the most common, and in the end gives a brief overview of warnings statistics and the most recent evaluation. According to the feedback from the firefighting community, the warnings proved to be important in the organization of supervisory and preventive activities, as well as fire suppression activities in case of vegetation fire ignition. The evaluation also shows that most of the significant vegetation fires burned in the days and at the locations for which warnings were issued.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.749
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0210.001

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 head0.008
GPT teacher head0.193
Teacher spread0.184 · 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