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Record W2992934910

Mechanical tree harvesters spread fungal inoculum onto freshly felled Canadian and New Zealand pine logs.

2004· article· en· W2992934910 on OpenAlexaboutno aff
Adnan Uzunovic, Diahanna O'callahan, B. Kreber

Bibliographic record

VenueForest Products Journal · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPinus radiataBark (sound)OphiostomaFungusRadiataAureobasidium pullulansBiologyBotanyPinus contortaInoculationTree healthPine woodMycologyHorticultureEcology
DOInot available

Abstract

fetched live from OpenAlex

Mechanical tree harvesters damage the exterior of freshly felled logs, loosening and removing bark, and producing punctures and indentations up to several centimeters deep. Damaged logs are susceptible to invasion by a plethora of wood-inhabiting fungi. In this study, we investigated the role of tree harvesters in disseminating fungi, particularly wood-discoloring fungi, or inoculating Canadian lodgepole pine and New Zealand radiata pine logs. In the study reported here, wood-decaying fungi, staining fungi, and moulds were isolated from a harvester head and the bark of standing lodgepole pine trees. This microflora may be translocated into the sub-surface regions of logs during the harvesting process. In Canada, Aureobasidium pullulans was the most frequently isolated staining fungus followed by Ophiostoma minus and Leptographium spp. All were isolated from stained areas associated with damage sites. Sphaeropsis sapinea was the most prominent species in New Zealand. Tree harvesters clearly play a role in the dissemination of wood-degrading fungi into freshly felled conifer logs.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score0.960

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 studies0.0010.000
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 head0.021
GPT teacher head0.193
Teacher spread0.172 · 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 teacher head, 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

Citations11
Published2004
Admission routes1
Has abstractyes

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