MétaCan
Menu
Back to cohort
Record W2160184505 · doi:10.1109/oceans.1993.326195

A command, control and communications interface for an environmental sampling ROV

2002· article· en· W2160184505 on OpenAlexaff
D.J. MacQuarrie, L.R. Cosby, C. Edley, W.A. Gallant

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsInterface (matter)Remotely operated underwater vehicleSoftwareCommand and controlSampling (signal processing)Computer scienceUser interfaceControl (management)Mission control centerEmbedded systemOperating systemHuman–computer interactionSystems engineeringEngineeringTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

Design and implementation of a command, control, communications (C/sup 3/) interface for a low-cost environmental sampling ROV (Erebus) is presented as a case study. The interface is designed to use existing technologies to provide a low-cost, easily operated console that could be easily modified. The console was designed and tested entirely in software, with all necessary piloting information presented on a single large monitor. The software was designed using a combination of rapid prototyping and informal specification. Various benefits of such a design are noted, as well as several problems encountered. Although this type of interface may not appear practical for single-mission ROVs, it has many advantages which makes it an attractive alternative for student research vehicles such as this.>

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.131
GPT teacher head0.334
Teacher spread0.203 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Software Engineering MethodologiesFrench-language works237,207