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Record W6992908948

MOTAN: A Novel Approach for determining Ice-Induced Global Loads on Ships.

2003· article· en· W6992908948 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.

fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNPARC · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicLanguage, Communication, and Linguistic Studies
Canadian institutionsnot available
FundersTransport Canada
KeywordsFocus (optics)Sea iceTransient (computer programming)SoftwareData processingData collection
DOInot available

Abstract

fetched live from OpenAlex

This paper introduces an inertial measurement system called MOTAN and discusses results from one of its full-scale installations. Recent measurements have shown that the MOTAN system offers a novel approach for determining ice-induced global loads on ships. The system consists of two parts: an instrument for measuring whole-ship motions, and software for processing those motions to obtain global ice impact loads. A background of the MOTAN system is given, along with modelscale and full-scale data to support its feasibility for determining global loads from transient ice impacts. The focus of the paper is full-scale data acquired while the CCGS LOUIS S. STLAURENT rammed old ice floes in the high Arctic. MOTAN-derived global loads are presented for three representative events. Data show that ice impact forces can approach 17.3 MN when ships operate in heavy ice conditions.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.094
GPT teacher head0.363
Teacher spread0.269 · 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