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Record W3109334768

선박 근접상황에서 항해사의 인적특성요인이 지각한 충돌위험도에 미치는 영향에 관한 연구

2020· article· ko· W3109334768 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venue해양환경안전학회지 · 2020
Typearticle
Languageko
FieldSocial Sciences
TopicEducation, Safety, and Science Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCollisionLicenseQuarter (Canadian coin)StatisticsPsychologyDemographyApplied psychologyComputer securityComputer scienceGeographyMathematics
DOInot available

Abstract

fetched live from OpenAlex

This study focuses on the margin of human error when a navigator is embarrassed by the psychological fear of collision in a close-quarter situation (CQS) and is unable to perform as per the prescribed collision avoidance measures. The purpose of the study is to identify the effects of the navigator's personal characteristics or factors in relation to on-board career (OC), license rating (LR), and age on the perceived collision risk (PCR) in CQSs. In order to obtain quantified data regarding the collision risk perceived by the navigator in four typical CQSs between their own ship and a target ship, this study measured and collated the heart rate variability of 30 navigators on their own ship when two ships approached each other at a speed of 10 knots from 2.5 nautical miles to a collision situation. According to a multiple regression analysis of the measured values, the navigators’ OC and LR factors had negative effects on the PCR, while the age factor had no significant effect on PCR. The t-test results showed that the PCR value was significantly higher for navigators with an OC ≤ 4 years than for those with an OC ≥ 5 years, and the LR factor was significantly higher for a class 4∼6 group than for a class 2∼3. This finding may be applied to the development of collision risk warning systems, particularly for navigators.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.081
GPT teacher head0.368
Teacher spread0.287 · 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