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Record W1931483688 · doi:10.24908/pceea.v0i0.5862

DELIVERY OF A GRADUATE COURSE IN FIRE PERFORMANCE TESTING USING VIDEOCONFERENCE TECHNOLOGY

2015· article· en· W1931483688 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsUniversity of WaterlooUniversity of Saskatchewan
Fundersnot available
KeywordsCourseworkVideoconferencingModular designFire safetyEngineering managementComputer scienceEngineeringMedical educationMultimediaCivil engineeringMedicine

Abstract

fetched live from OpenAlex

There is a growing demand for fire safetyengineers. While new fire safety engineering programshave been created, the demand for highly qualifiedpersonnel is growing more rapidly than the supply of newgraduates. One particular challenge is the ability of asingle institution to offer the range of courses required ina comprehensive fire safety engineering program.Fire Performance Testing and other courses in theUW Fire Safety Engineering program are offered in amodular format: lectures are given over one week, andstudents submit coursework over the following four to sixmonths. This format allows a larger number of practicingengineers and faculty from other universities to take orteach courses. This paper focuses on the use ofvideoconference technology in ME 770. Since 2012 abouthalf of the students, and one of the instructors, have takenthe course or delivered their lectures by videoconference.Lessons learned, and efforts to establish modular firecourses with other universities, will also be discussed.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.053
GPT teacher head0.276
Teacher spread0.223 · 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