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Failure to Detect Critical Auditory Alerts in the Cockpit

2013· article· en· 159 citations· W2031317277 on OpenAlex· 10.1177/0018720813510735

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Insufficient payload (model declined to judge)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: ObservationalConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.864
Threshold uncertainty score
0.998
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.032
GPT teacher head0.323
Teacher spread
0.291 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

OBJECTIVE: The aim of this study was to test whether inattentional deafness to critical alarms would be observed in a simulated cockpit. BACKGROUND: The inability of pilots to detect unexpected changes in their auditory environment (e.g., alarms) is a major safety problem in aeronautics. In aviation, the lack of response to alarms is usually not attributed to attentional limitations, but rather to pilots choosing to ignore such warnings due to decision biases, hearing issues, or conscious risk taking. METHOD: Twenty-eight general aviation pilots performed two landings in a flight simulator. In one scenario an auditory alert was triggered alone, whereas in the other the auditory alert occurred while the pilots dealt with a critical windshear. RESULTS: In the windshear scenario, II pilots (39.3%) did not report or react appropriately to the alarm whereas all the pilots perceived the auditory warning in the no-windshear scenario. Also, of those pilots who were first exposed to the no-windshear scenario and detected the alarm, only three suffered from inattentional deafness in the subsequent windshear scenario. CONCLUSION: These findings establish inattentional deafness as a cognitive phenomenon that is critical for air safety. Pre-exposure to a critical event triggering an auditory alarm can enhance alarm detection when a similar event is encountered subsequently. APPLICATION: Case-based learning is a solution to mitigate auditory alarm misperception.

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.

The record

Venue
Human Factors The Journal of the Human Factors and Ergonomics Society
Topic
Human-Automation Interaction and Safety
Field
Psychology
Canadian institutions
Université Laval
Funders
not available
Keywords
ALARMCockpitFalse alarmAeronauticsInattentional blindnessAviationWarning systemPsychologyComputer scienceAudiologyEngineeringPerceptionMedicineTelecommunicationsArtificial intelligence
Has abstract in OpenAlex
yes