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Record W1992782386 · doi:10.3390/ma3125311

Evaluation of Compatibility between Beetle-Killed Lodgepole Pine (Pinus Contorta var. Latifolia) Wood with Portland Cement

2010· article· en· W1992782386 on OpenAlexaff
Sorin Aurelian Pașca, Ian D. Hartley, Ronald W. Thring

Bibliographic record

VenueMaterials · 2010
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsPinus contortaMountain pine beetlePortland cementCompatibility (geochemistry)CementWhite rotDendroctonusBotanyHorticulturePulp and paper industryEnvironmental scienceComposite materialMaterials scienceBiologyEcologyBark beetleLigninEngineering

Abstract

fetched live from OpenAlex

The compatibility of wood from mountain pine beetle (Dendroctonus ponderosa) killed lodgepole pine (Pinus contorta var. latifolia) with Portland cement was investigated based on time-since-death as a quantitative estimator, and the presence of blue-stained sapwood, brown rot, or white rot as qualitative indicators. The exothermic behavior of cement hydration, maximum heat rate, time to reach this maximum, and total heat released within a 3.5-24 h interval were used for defining a new wood-cement compatibility index (CX). CX was developed and accounted for large discrepancies in assessing wood-cement compatibility compared to the previous methods. Using CX, no significant differences were found between fresh or beetle-killed wood with respect to the suitability for cement; except for the white rot samples which reached or exceeded the levels of incompatibility. An outstanding physicochemical behavior was also found for blue-stained sapwood and cement, producing significantly higher compatibility indices.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 science0.0000.000
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 head0.032
GPT teacher head0.248
Teacher spread0.216 · 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 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

Citations22
Published2010
Admission routes1
Has abstractyes

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