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Record W2566219180 · doi:10.1139/cjb-2016-0245

Fire and dwarf mistletoe (Viscaceae: <i>Arceuthobium</i> species) in western North America: contrasting <i>Arceuthobium tsugense</i> and <i>Arceuthobium americanum</i>

2016· article· en· W2566219180 on OpenAlexvenueno aff
David C. Shaw, Michelle C. Agne

Bibliographic record

VenueBotany · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
FundersDivision of Materials Research
KeywordsBiologyEcologyPinus contortaFire ecologyHost (biology)Western HemlockBotanyEcosystem

Abstract

fetched live from OpenAlex

Dwarf mistletoes (Viscaceae: Arceuthobium spp.) and fire interact in important ways in the coniferous forests of western North America. Fire directly affects dwarf mistletoes by killing the host, host branch, or heating/smoking the aerial shoots and fruits. Fire is a primary determinant of dwarf mistletoe distribution on the landscape, and time since fire controls many aspects of dwarf mistletoe epidemiology. Conversely, dwarf mistletoes can influence fire by causing changes in forest composition, structure, and fuels. Prescribed fire is important for management of dwarf mistletoes, while fire suppression is thought to have increased dwarf mistletoe abundance in western forests. Two dwarf mistletoes are compared in order to illustrate fire interactions in Oregon and Washington, USA: Arceuthobium americanum Nutt. ex Engelm. (lodgepole pine dwarf mistletoe) and Arceuthobium tsugense (Rosendahl)(western hemlock dwarf mistletoe). Arceuthobium persists on the landscape where the host is not killed by fire. Arceuthobium americanum spreads directly into the regenerating Pinus contorta Dougl. ex Loud., while A. tsugense persists in refugia for 200 years or more following fire. Host successional status is a driver of fire – dwarf mistletoe interactions, but forest disturbance agents also play a role. Given the importance of these interactions to the ecology of fire-prone forests, dwarf mistletoes warrant inclusion in disturbance ecology research.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.208
Teacher spread0.193 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

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