Fungi attacking historic wood of Fort Conger and the Peary Huts in the High Arctic
Bibliographic record
Abstract
Historic wooden structures in Polar Regions are being adversely affected by decay fungi and a warming climate will likely accelerate degradation. Fort Conger and the Peary Huts at Lady Franklin Bay in northern Ellesmere Island are important international heritage sites associated with early exploration in the High Arctic. Fort Conger, built by Adolphus Greely and expedition members during the First International Polar Year in 1881, was dismantled and used by Robert Peary and his expedition crew in the early 1900's to build several smaller shelters. These historic structures remain at the site but are deteriorating. This investigation examines the fungi associated with wood decay in the historic woods. Soft rot was observed in all 125 wood samples obtained from the site. The major taxa found associated with the decayed wood were Coniochaeta (18%), Phoma (13%) Cadophora (12%), Graphium (9%), and Penicillium (9%) as well as many other Ascomycota that are known to cause soft rot in wood. Micromorphological observations using scanning electron microscopy of historic wooden timbers that were in ground contact revealed advanced stages of type I soft rot. No wood destroying Basidiomycota were found. Identification of the fungi associated with decay in these historic woods is a first step to better understand the unusual decomposition processes underway in this extreme environment and will aid future research to help control decay and preserve this important cultural heritage.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".