MétaCan
Menu
Back to cohort
Record W2296781809 · doi:10.1080/07373937.2015.1114950

Impact of airflow on hem-fir kiln drying

2016· article· en· W2296781809 on OpenAlex
John W. Wallace, Stavros Avramidis

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.

Bibliographic record

VenueDrying Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAirflowKilnWood dryingEnvironmental scienceMoistureShrinkageEvaporationWater contentWork (physics)HumidityPulp and paper industryMeteorologyWaste managementMaterials scienceComposite materialEngineeringMechanical engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

The skill in optimized lumber drying lies in controlling the rate of evaporation to match the rate at which moisture reaches the surface; the aim is to minimize the moisture gradient without damaging the lumber. Adjustable speed drives have proven themselves as a method for reducing energy consumption by reducing fan speed in the later stages of drying to match the rate of evaporation. Little work has been done to investigate how lower air velocities over the lumber stack during the later stages of drying affects quality of the final product in terms of moisture content distribution, shrinkage, and degrade. This study was undertaken to examine the impact of airflow using an adjustable speed drive on the final quality of 50 × 152.5 mm Pacific Coast Hemlock.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.379

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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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