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From Lilliput to Brobdingnag: Extending Models of Mycorrhizal Function across Scales

2006· article· en· W2141704722 on OpenAlexafffund
Nancy Collins Johnson, Jason D. Hoeksema, James D. Bever, V. Bala Chaudhary, Catherine A. Gehring, John N. Klironomos, Roger T. Koide, R. M. Miller, John C. Moore, Peter Moutoglis, Mark W. Schwartz, Suzanne W. Simard, William A. Swenson, James Umbanhowar, Gail W. T. Wilson, Catherine A. Zabinski

Bibliographic record

VenueBioScience · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of British ColumbiaUniversity of Guelph
FundersDivision of Environmental BiologyNatural Sciences and Engineering Research Council of CanadaBiological and Environmental ResearchUniversity of California, Santa Barbara
KeywordsEcosystemEcologyTerrestrial ecosystemEnvironmental resource managementSustainabilityGlobal changeTemporal scalesPopulationScale (ratio)Ecosystem servicesProductivityEnvironmental scienceBiologyGeographyClimate change

Abstract

fetched live from OpenAlex

Mycorrhizae occur in nearly all terrestrial ecosystems. Resource exchange between host plants and mycorrhizal fungi influences community, ecosystem, and even global patterns and processes. Understanding the mechanisms and consequences of mycorrhizal symbioses across a hierarchy of scales will help predict system responses to environmental change and facilitate the management of these responses for sustainability and productivity. Conceptual and mathematical models have been developed to help understand and predict mycorrhizal functions. These models are most developed for individual- and population-scale processes, but models at community, ecosystem, and global scales are also beginning to emerge. We review seven types of mycorrhizal models that vary in their scale of resolution and dynamics, and discuss approaches for integrating these models with each other and with general models of terrestrial ecosystems.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.016
GPT teacher head0.228
Teacher spread0.211 · 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 designTheoretical or conceptual
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

Citations90
Published2006
Admission routes2
Has abstractyes

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