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3rd European Symposium on Fire Safety Science

2018· article· en· W2947364688 on OpenAlexaboutno aff
Pascal Boulet, Bart Merci, Patrick Van Hees

Bibliographic record

VenueJournal of Physics Conference Series · 2018
Typearticle
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsnot available
Fundersnot available
KeywordsFire safetyPresentation (obstetrics)Library sciencePolitical scienceEngineering ethicsEngineeringMedicineComputer scienceCivil engineering

Abstract

fetched live from OpenAlex

Pascal BOULET 1 , Bart MERCI 2 and Patrick VAN HEES 3 1 Université de Lorraine, CNRS, LEMTA, France 2 Ghent University, Department of Fluid Mechanics, Heat and Combustion, Ghent, Belgium 3 Lund University, Division of Fire Safety Engineering, Lund, Sweden pascal.boulet@univ-lorraine.fr EDITORIAL This special issue is based on the papers selected for presentation during the 3 rd ESFSS (European Symposium on Fire Safety Science) , held in Nancy (France) from 12 to 14 September 2018. Following the conference held in Cyprus (2015), the 3rd ESFSS was the third edition of a series of symposia organized in Europe, with the participation and support of the International Association for Fire Safety Science (IAFSS). The aim was to gather researchers from within Europe and beyond to have exchanges and discussions about fire safety science. In this frame, a workshop Agenda 2030 for a Fire Safe World was also organized by IAFSS on the afternoon of Tuesday, September 11, prior to the symposium, with the aim to discuss the definition of a Fire Safety Mission and the identification of specific topics for fire science research. Around 120 contributions have been received during the conference preparation, involving both submissions for oral and poster presentation. A selection, based on two peer-reviews of full papers, finally conducted to the acceptance of 35 contributions for oral presentation and 55 for poster presentation, plus 11 posters in a special session dedicated to work-in-progress. The conference was attended by 140 scientists, coming not only from Europe but from around the world, namely from Australia, Belgium, Canada, China, Czech Republic, Finland, France, Germany, India, Indonesia, Ireland, Japan, Portugal, Russia, Slovenia, Spain, Sweden, Turkey, United Kingdom, USA. List of Symposium chair and Scientific committee are available in this PDF.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.400

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 communication0.0000.001
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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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.

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

Citations4
Published2018
Admission routes1
Has abstractyes

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