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Record W2071030038 · doi:10.1080/00140139.2014.943680

Establishment of performance standards and a cut-score for the Canadian Forces Firefighter Physical Fitness Maintenance Evaluation (FF PFME)

2014· article· en· W2071030038 on OpenAlex
W. Todd Rogers, David Docherty, Stewart R. Petersen

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueErgonomics · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsUniversity of AlbertaUniversity of Victoria
Fundersnot available
KeywordsFirefightingWork (physics)Set (abstract data type)Physical fitnessAeronauticsSimulationComputer scienceEngineeringMedicinePhysical therapyMechanical engineeringGeography

Abstract

fetched live from OpenAlex

The bookmark method for setting cut-scores was used to re-set the cut-score for the Canadian Forces Firefighter Physical Fitness Maintenance Evaluation (FF PFME). The time required to complete 10 tasks that together simulate a first-response firefighting emergency was accepted as a measure of work capacity. A panel of 25 Canadian Forces firefighter supervisors set cut-scores in three rounds. Each round involved independent evaluation of nine video work samples, where the times systematically increased from 400 seconds to 560 seconds. Results for Round 1 were discussed before moving to Round 2 and results for Round 2 were discussed before moving to Round 3. Accounting for the variability among panel members at the end of Round 3, a cut-score of 481 seconds (mean Round 3 plus 2 SEM) was recommended. Firefighters who complete the FF PFME in 481 seconds or less have the physical capacity to complete first-response firefighting work.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.052
GPT teacher head0.394
Teacher spread0.341 · 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