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Record W4252930210 · doi:10.1109/pcicon.2012.6549665

Electrical heat tracing for surface heating on arctic vessels & structures to prevent snow & ice accumulation

2012· article· en· W4252930210 on OpenAlexaff
H. Brazil, Bob Conachey, Gary Savage, P.R. Baen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsAtlantic Industries (Canada)
Fundersnot available
KeywordsSnowAmpereTracingMaterials scienceChemistryGeologyOceanographyComputer scienceCurrent (fluid)Geomorphology

Abstract

fetched live from OpenAlex

The Proposed “IEEE 45.8 Recommended Practice for Electrical Installations on Shipboard - Cable Systems” will reference EHT (Electrical Heat Trace) for heating pipes, tanks, and instrumentation on-board ocean-going vessels. The globally recognized IEEE 515 Standard for resistance heat tracing addresses “traditional” freeze protection and temperature maintenance applications on-board tankers and FPSO (Floating Production, Storage, and Offloading) facilities, but not for keeping un-insulated surfaces above freezing. As fossil fuels are discovered offshore in arctic regions, their development requires increasing resources to prevent the accumulation (or melting) of snow and ice. Outdoor stairs, handrails, walkways, and other exposed and un-insulated surfaces require protection in these harsh environments. These represent growing requirements for EHT to be installed on, in or under surfaces to reduce unsafe conditions during normal operations or during emergency 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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.004

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 head0.041
GPT teacher head0.298
Teacher spread0.256 · 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 designNot applicable
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

Citations3
Published2012
Admission routes1
Has abstractyes

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