MétaCan
Menu
Back to cohort
Record W2554915633 · doi:10.1049/iet-cta.2016.0930

Robust consensus of autonomous underactuated surface vessels

2016· article· en· W2554915633 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIET Control Theory and Applications · 2016
Typearticle
Languageen
FieldComputer Science
TopicDistributed Control Multi-Agent Systems
Canadian institutionsConcordia University
FundersQatar National Research Fund
KeywordsUnderactuationUnmanned surface vehicleControl theory (sociology)Computer scienceSurface (topology)Control engineeringEngineeringArtificial intelligenceMathematicsRobotControl (management)Marine engineeringGeometry

Abstract

fetched live from OpenAlex

A distributed robust consensus of multiple autonomous underactuated surface vessels (AUSV) is studied in the presence of unknown environmental disturbances. The vehicles have 3 degrees of freedom and two actuators. Since the actuated and unactuated states of the vehicles are strongly coupled, first their kinematics and dynamics are transformed to a cascade non‐linear system. Then, based on the properties of non‐linear cascade systems, a state‐based switching controller is proposed which guarantees the robust consensus of AUSVs. To illustrate the performance of the proposed consensus approach, simulation results are provided.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.232
Teacher spread0.216 · 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