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Record W2124849318 · doi:10.1071/hr14004

From Science to Heritage: the History of a Wood Collection

2014· article· en· W2124849318 on OpenAlexaff
John Dargavel, Philip D. Evans, Gordon Dadswell

Bibliographic record

VenueHistorical Records of Australian Science · 2014
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCommonwealthCultural heritageHistory of scienceLibrary scienceHistorical recordEngineeringArchaeologyGeographyMemoirHistoryArt historyComputer science

Abstract

fetched live from OpenAlex

There is a process by which scientific collections become heritage. The case of a wood collection, or xylarium, at the Australian National University (ANU) is discussed from its start in the Commonwealth Forestry Bureau in 1926, its association with the Council for Scientific and Industrial Research/Commonwealth Scientific and Industrial Research Organisation from 1928, its transfer to ANU in 1965, its manifold uses at ANU, and its decline and heritage assessment in 2011. The collection, consisting of 8,400 wood samples, microscope slides, panels and artefacts, was used for teaching forestry students, research into wood anatomy, and for identifying timber. Its future is uncertain.

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0190.025
Scholarly communication0.0100.011
Open science0.0020.007
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0130.002

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 head0.030
GPT teacher head0.232
Teacher spread0.202 · 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 designObservational
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
Published2014
Admission routes1
Has abstractyes

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