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Record W1577288293 · doi:10.4271/2005-01-1198

Off-Throttle Turning Performance of Personal Watercraft for Accident Reconstruction

2005· article· en· W1577288293 on OpenAlexaff
Craig A. Good, Marshal H. Paulo, Lonnie J. Unger, Janine L. Varga, M. C. B. Ellis

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2005
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsWatercraftThrottleAutomotive engineeringCruise controlComputer scienceEngineeringControl (management)Marine engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Lack of operator control during off-throttle steering probably has contributed to many personal watercraft (PWC) collisions. Most PWCs are not equipped with any type of off-throttle steering devices. In this study, the average off-throttle steering trajectories were investigated for four commercially available PWCs at a test speed of 30 mph. An add-on device was tested on one of the PWCs to determine whether off-throttle turning performance could be improved. The off-throttle performance of a 16 ft runabout with a 140 hp outboard motor was also tested for comparison. The watercraft were tested according to the SAE J2608 Recommended Practice, Off-Throttle Steering Capabilities of Personal Watercraft. The trajectories of these watercraft were quantified in an off-throttle steering maneuver. These trajectories can be used as a guideline to reconstruct PWC accidents. The off-throttle turning capabilities of the test watercraft can be classified into two categories: those with effective off-throttle turning capability and those without effective off-throttle turning capability. Results showed that PWCs not equipped with an off-throttle steering device had virtually no turning capabilities. PWCs with off-throttle steering devices demonstrated substantially enhanced turning capabilities. The runabout also demonstrated superior off-throttle steering performance.

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations1
Published2005
Admission routes1
Has abstractyes

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