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Record W37503158 · doi:10.5006/c2009-09172

Evaluating the Corrosiveness of Southern Pine Treated with Several Wood Preservatives Using Electrochemical Techniques

2009· article· en· W37503158 on OpenAlexaff
Samuel L. Zelinka, Douglas R. Rammer, Donald S. Stone

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsNorbord (Canada)
Fundersnot available
KeywordsPreservativeElectrochemistryPulp and paper industryPine woodMaterials scienceCorrosionEnvironmental scienceComposite materialChemistryElectrodeEngineeringOrganic chemistryBotany

Abstract

fetched live from OpenAlex

Abstract Chromated copper arsenate (CCA), the most widely used wood preservative of the past 50 years, has been replaced for most uses with alkaline-copper systems such as alkaline copper quaternary (ACQ), copper azole (CuAz) and micronized copper quaternary (MCQ). Preliminary research using high-temperature, high-humidity environments have shown that some of these wood preservatives are more corrosive than CCA, although it is unclear how the results of these extreme tests correlate to performance at temperatures and humidities seen in-service. Recently, the authors developed an electrochemical method for rapid determination of the corrosion rate for fasteners in water extracts of treated wood. The authors have previously demonstrated good correlation between the electrochemical-extract test and exposure tests of fasteners in ACQ treated Southern pine. This work uses the electrochemical-extract method to examine corrosion of carbon steel and galvanized steel on untreated southern pine, as well as southern pine treated with five different wood preservatives.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

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

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 head0.053
GPT teacher head0.340
Teacher spread0.287 · 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.

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

Citations7
Published2009
Admission routes1
Has abstractyes

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