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Record W2136102967 · doi:10.1109/oceans.1996.572817

Dynamic coefficient estimation using variational and least-squares techniques

2002· article· en· W2136102967 on OpenAlexaff
Frederick Driscoll, Rolf G. Lueck

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTension (geology)Least-squares function approximationComputer scienceControl theory (sociology)Surface tensionRosette (schizont appearance)MechanicsMathematicsPhysicsClassical mechanicsThermodynamicsStatisticsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents a variational and least-squares technique for determining the dynamic coefficients of a tethered marine platform, the IOS WOCE Rosette Sampler. The virtue of these techniques is that they use data (pressure and tether tension) acquired during normal profiling operations and do not require any special procedures. The measured cable tension agrees closely with the tension predicted by a mathematical model of the Rosette Sampler. The derived coefficients can be used in models of the ship-tether-platform system to predict the occurrence of zero cable tension and the subsequent snap loads which can damage, and possibly break, the tether.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.042
GPT teacher head0.277
Teacher spread0.235 · 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.

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

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