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Record W7110461724

Critically evaluating the need for specialty teams for high-rise firefighting

2025· article· en· W7110461724 on OpenAlexaboutno aff

Bibliographic record

VenueSHAREOK (University of Oklahoma; Oklahoma State University; Central Oklahoma University) · 2025
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsFirefightingSpecialtyScope (computer science)First responderKey (lock)ALARM
DOInot available

Abstract

fetched live from OpenAlex

High-rise fires are high-risk, low-frequency events that pose significant challenges for fire department personnel. When confronted with a high-rise fire incident commanders often have to make critical decisions with limited information due to their inability to properly size-up/assess the building due to its size. As the incident progresses building construction features along with items such as the fire alarm control panel, fire pumps, standpipes, stairwells, elevators, and smoke removal systems become key elements used to access and suppress the fire. However, it is not uncommon for these items to malfunction or fail as the operation is taking place thus requiring specialists to intervene. Therefore, this study aims to critically evaluate the need for specialty teams for high-rise firefighting. The aim is supported by three objectives: 1) evaluation of the need for utilizing specialty teams in ambiguous situations that can arise during high-rise firefighting that go beyond the scope of basic training; 2) identify how a specialty team for high-rise firefighting can be utilized and structured by conducting semi-structured interviews with subject matter experts; 3) determine if pros and cons of establishing a team that specializes in high-rise firefighting can exist and how either would impact the effectiveness of the overall operation. This study employed a pragmatic approach using inductive reasoning to answer three research questions: 1) could the use of a specialty team for high-rise firefighting provide a significant impact that will affect the outcomes of a high-rise fire; 2) what is the best approach for fighting a high-rise fire; 3) is there a need for specialty teams for high-rise firefighting. In order to answer these questions semi-structured interviews were conducted with 28 retired and current incident commanders within the US and Canada. As a result five themes, 12 categories, and 62 codes emerged. The five themes of Training, Incident Commander Considerations, Size-up, Deployment and Use of a Specialty Team, and Considerations for a Specialty Team supported the need for a specialty team for high-rise firefighting.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.021
GPT teacher head0.277
Teacher spread0.256 · 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.

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
Published2025
Admission routes1
Has abstractyes

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