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Record W2107780440 · doi:10.1002/maco.200604035

Corrosion resistance of hot‐dipped zinc and zinc alloy coated sheet steels under offshore atmospheric environment

2007· article· en· W2107780440 on OpenAlexaff
Y. Li, J. Liu, Yueming Li, Shaohua Chu

Bibliographic record

VenueMaterials and Corrosion · 2007
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCorrosionZincMetallurgyAlloyMaterials scienceCoatingAluminiumSubmarine pipelineSeawaterSalt (chemistry)Composite materialChemistryEngineeringGeology

Abstract

fetched live from OpenAlex

Abstract The application of hot‐dipped zinc and zinc‐aluminum alloy coatings were introduced. Exposure tests of the steels with these coatings were conducted in the offshore atmosphere in Qingdao and Xiamen for 12 years separately. Effects of the coating thickness, alloy composition and atmospheric environment on the corrosion performance were studied. Results of the onsite exposure tests were compared with the results of a previous indoor salt spray accelerated corrosion tests. The study supports that zinc‐aluminum alloy coatings are useful in providing better corrosion resistance and can be further developed for future applications.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.013
GPT teacher head0.231
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 teacher head, not a consensus.

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

Citations2
Published2007
Admission routes1
Has abstractyes

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