MétaCan
Menu
Back to cohort
Record W2079032517 · doi:10.1017/s0373463304002668

Simulated Navigation Performance with Marine Electronic Chart and Information Display Systems (ECDIS)

2004· article· en· W2079032517 on OpenAlexaffabout
D. C. Donderi, Robert R. Mercer, Ma Hong, Douglas J. Skinner

Bibliographic record

VenueJournal of Navigation · 2004
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsMcGill University
Fundersnot available
KeywordsOverlayRadarComputer scienceChartVisibilityRemote sensingReal-time computingTelecommunicationsMeteorologyGeologyGeography

Abstract

fetched live from OpenAlex

Licensed mariners carried out two simulated navigation studies testing electronic chart and information display systems (ECDIS) against paper chart navigation. In the first study, six mariners each completed approaches to Halifax, Nova Scotia, harbour with good and bad visibility and a range of wind and currents. Conditions included chart with radar, ECDIS with radar overlay and ECDIS with separate radar. ECDIS produced better performance and a smaller workload than paper charts and the radar overlay was slightly better than the separate radar display. In the second study, six new mariners completed exercises with low visibility and heavy or light radar traffic using ECDIS with radar overlay, ECDIS without overlay and ECDIS with optional overlay. Mariners preferred the optional overlay but all three conditions produced about equal performance. Based on mariners' performance and expressed preference, we recommend that ECDIS systems provide optional radar overlays.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.002
GPT teacher head0.179
Teacher spread0.177 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations17
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueJournal of NavigationSame topicMaritime Navigation and SafetyFrench-language works237,207