MétaCan
Menu
Back to cohort
Record W2137154648 · doi:10.1177/154193120705102601

Studying Complex Human-System Behaviour: Human-in-the-loop Simulation Requirements

2007· article· en· W2137154648 on OpenAlexfundno aff
David Crone, Penelope Sanderson, Neelam Naikar

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2007
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsnot available
FundersDefence Research and Development Canada
KeywordsProcurementAircrewFidelityComputer scienceFrame (networking)Task (project management)Work (physics)Systems engineeringOperations researchEngineeringSimulationAeronautics

Abstract

fetched live from OpenAlex

The Defence Science and Technology Organisation (DSTO) is required to provide advice to customers for the procurement of future military systems using the high fidelity human-in-the-loop simulation (HILS) facility housed in the Air Operations Simulation Centre (AOSC). A program of research is under way that compares two work analysis techniques (traditional task analysis and Cognitive Work Analysis) on the basis of whether the human-system performance measures that they suggest are sensitive to system modifications and so may be used for system evaluation. In this paper we show that representing aircrew's tactical environment as a series of concentric “rings” resulted in the development of HILS requirements that let us evaluate the measures derived from both work analysis approaches. Using the rings to frame the experiment and develop simulation requirements was beneficial for several reasons including participant involvement, validity of the system and operator behaviour observed, and completeness of the study.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score1.000

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 head0.082
GPT teacher head0.370
Teacher spread0.288 · 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 designObservational
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

Citations3
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Human Factors and Ergonomics Society Annual MeetingSame topicHuman-Automation Interaction and SafetyFrench-language works237,207