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Record W4300622768 · doi:10.5957/icetech-2008-174

Probabilistic Pipeline Burial Analysis for Protection against Ice Scour

2008· article· en· W4300622768 on OpenAlex
Tony King, Ryan Phillips, J. Barrett

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsSeabedIcebergProbabilistic logicKeelPipeline (software)GeologyRange (aeronautics)Stress (linguistics)Probabilistic analysis of algorithmsReliability (semiconductor)Marine engineeringPipeline transportGeotechnical engineeringEngineeringOceanographySea iceStatisticsAerospace engineeringMathematics

Abstract

fetched live from OpenAlex

A probabilistic burial analysis for protection against iceberg scouring of the seabed is presented for a hypothetical pipeline on the Grand Banks off Canada’s east coast. The analysis procedure combines a probabilistic characterization of the iceberg scour regime with a deterministic analysis of pipeline stress/strain response for a range of iceberg scour widths, depths and iceberg keel/pipeline crown clearances, allowing pipeline burial to be defined using specified stress/strain limits and target reliability levels.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.233
Teacher spread0.207 · 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