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Record W4238470014 · doi:10.1002/9781119701125.ch14

Softwoods Used in Construction – With Their Main Properties and Sustainability Credentials

2020· other· en· W4238470014 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicCivil and Structural Engineering Research
Canadian institutionsnot available
Fundersnot available
KeywordsWestern HemlockSustainabilitySoftwoodEuropean marketGeographyForestryWestern europeEngineeringEuropean unionBusinessPulp and paper industryInternational tradeEcologyBiology

Abstract

fetched live from OpenAlex

This chapter describes a timber’s general appearance, then provides an indication of its average density (weight), and goes on through all its main characteristics. It begins with the softwoods, which tend very much to be the ‘workhorses’ of the wood-using industries. They are used extensively in most normal construction. The chapter outlines the two timbers most commonly used in the United Kingdom and Europe, known almost universally within the timber trade by their common names, ‘European redwood’ and ‘European whitewood’. In terms of the ‘sustainability’ credentials of both European whitewood and British spruce, they are much the same as for European redwood. Douglas fir is a native of western North America, growing in pretty much the same areas as Western hemlock, most abundantly in British Columbia in Canada and in Washington and Oregon in the United States.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.702
Threshold uncertainty score0.585

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 head0.012
GPT teacher head0.200
Teacher spread0.188 · 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