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Record W1984946958 · doi:10.3188/szf.2004.0263

La gestione degli incendi boschivi in Canton Ticino: tentativo di una sintesi storica | Forest fire management in Canton Ticino: attempting a historical overview

2004· article· en· W1984946958 on OpenAlexaff
Marco Conedera, Gabriele Corti, Paolo Piccini, Daniele Ryser, Francesco Guerini, Ivo Ceschi

Bibliographic record

VenueSchweizerische Zeitschrift fur Forstwesen · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsGeographyFire protectionElectrificationForestryEnvironmental protectionEnvironmental resource managementEnvironmental scienceEngineeringCivil engineering

Abstract

fetched live from OpenAlex

The Southern Alps, in particular the Canton Ticino, is the region of Switzerland that is most affected by the phenomenon of forest fires. Therefore, the cantonal authorities are continually confronted with problems of prevention, fire fighting and mitigation of the effects of forest fires. In this article forest fire management in Canton Ticino is analyzed in historical terms, verifying in particular the impact of the methods used and the improvement of technology addressing the frequency of events and the extent of burned surfaces. In this way it has been possible to show how a few structural measures (better organization of fire fighting crews and equipment, introduction of aerial fire fighting techniques, electrification followed by construction of shelters along railway lines, etc.) have rather reduced the extent of burned surfaces, while legislative measures such as restrictions of open fires help to reduce the number of forest fires.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.511

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.254
Teacher spread0.240 · 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 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

Citations17
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueSchweizerische Zeitschrift fur ForstwesenSame topicFire effects on ecosystemsFrench-language works237,207