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Record W7005077358

Proceedings from the Seventh International Symposium on Tunnel Safety and Security, ISTSS, Montréal, Canada, March 16-18, 2016

2016· article· en· W7005077358 on OpenAlexaboutno aff

Bibliographic record

VenueKTH Publication Database DiVA (KTH Royal Institute of Technology) · 2016
Typearticle
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)George (robot)Fire safetyPort (circuit theory)National securityPanel discussion
DOInot available

Abstract

fetched live from OpenAlex

This report includes the Proceedings of the 7th International Symposium on Tunnel Safety and Security (ISTSS) held in Montreal, Canada, 16-18 th of March, 2016. The Proceedings include 59 papers given by session speakers and 9 extended abstracts presenting posters exhibited at the Symposium. The papers were presented in 17 different sessions. Among them are Emergency Management, Passive Protection, Case Studies, Safety Levels and Acceptable Risks, Fixed Fire Fighting Systems, Security and Safe Operations, Regulations, Testing and Design, Risk Analysis, Ventilation, Evacuation and Fire Dynamics. Each day was opened by invited Keynote Speakers (in total six) addressing broad topics of pressing interest. The Keynote Speakers, selected as leaders in their field, consisted of Alexandre Debs, Ministére des Transports du Québec, Canada, Gary English, City of Seattle Fire Department, USA, Tony Cash, Transport for London, UK, Ahmend Kashef, National Research Council of Canada, George Hadjisophocleous, Carleton University of Canada and Harold L. Levitt, The Port Authority of New York and New Jersey, USA. We are grateful that the keynote speakers were able to share their knowledge and expertise with the participants of the symposium.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.983

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 science0.0010.000
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 head0.006
GPT teacher head0.200
Teacher spread0.194 · 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 designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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