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Record W6966492724 · doi:10.4224/20373946

International Road Tunnel Fire Detection Research Report - Phase II Task 1: Fire Detectors, Fire Scenarios and Test Protocols

2008· report· en· W6966492724 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2008
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
FundersFire Protection Research Foundation
KeywordsFire detectionTask (project management)Test (biology)Phase (matter)Fire safetyFire test

Abstract

fetched live from OpenAlex

This report presents the activities completed in Task 1 of the International Road Tunnel Fire Detection Research Project - Phase II. These activities include the selection of ten fire detection systems representing five types of currently available technologies for the fire test program. Each system meets the requirements established by the projects Technical Panel for the application of fire detection systems in tunnels, and meets the recommendations from Phase I of the project - Review of Prior Test Programs and Tunnel Fires. The five technology types are: linear heat detection systems, flame detectors, CCTV fire detectors,smoke detection systems and spot heat detectors. General information and operating principles of these systems are described in the report.

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)0.027
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.025

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 head0.097
GPT teacher head0.403
Teacher spread0.306 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2008
Admission routes1
Has abstractyes

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