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Record W7061286638

R-Class icebreaker propeller open water experiments

2002· other· en· W7061286638 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2002
Typeother
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsOpen waterPropellerTorqueData acquisitionSeal (emblem)Open seaBearing (navigation)
DOInot available

Abstract

fetched live from OpenAlex

In October 2002, propeller open water tests were performed using Memorial University's Opens Boat. The purpose of these experiments was to validate the creditability of the Opens Boat. The necessity of these experiments arose after several tests were performed using the MUN equipment that produced questionable results with regard to the torque values. The problems that were addressed during the testing procedure were: removal of an inner bearing in the Opens Boat to rectify the torque inconsistencies; a constant monitoring and recalibration of the shaft speed due to voltage variations during testing; and a temporary water seal on the Opens Boat to inhibit water ingress into the Open Boat during high carriage speed test runs. Once the problems with the Opens Boat were rectified, the results from the experiment were validated by comparison with tests performed earlier in Ottawa. Therefore, it is recommended that the Opens Boat should be utilized for future open water experiments. Other recommendations were also stated to ensure that the Opens Boat data would not be spoiled by other problems that may creep into the system. Some of these recommendations include: a replacement of the Data Acquisition System with a more reliable system that would include no exposed wires; a permanent sealant on all non-watertight joins; and a cover for the dynamometer.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.003

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 head0.020
GPT teacher head0.238
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 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
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

Citations0
Published2002
Admission routes2
Has abstractyes

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Same venueNPARCSame topicMagnetic Field Sensors TechniquesFrench-language works237,207