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Record W6887761080 · doi:10.17605/osf.io/mk3qe

Within British Columbia forested ecosystems, is the local species richness of vascular plants associated with the local dominance of ectomycorrhizal hosts?

2022· other· en· W6887761080 on OpenAlexaffabout

Bibliographic record

VenueOpen Science Framework · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpecies richnessDominance (genetics)SymbiosisUnderstoryMycorrhizaVascular plantPlant communityEcosystem

Abstract

fetched live from OpenAlex

In forest ecosystems, the vast majority of plants in both the canopy and understory form symbioses with mycorrhizal fungi. Mycorrhizal fungi form their symbioses by colonizing the plant’s roots either intracellularly, as is the case with arbuscular mycorrhizal fungi (AMF), or extracellularly as with ectomycorrhizal fungi (EMF). Mycorrhizal symbioses can range from being mutualistic to parasitic, influencing the plant’s carbon and nutrient cycling and pathogen defence. Recent research suggests that variations in the commonness and distribution of the different types of mycorrhizal symbioses (AMF versus EMF) can influence forest structure and functioning[1–4]. In particular, owing to their tendency to promote positive plant-soil feedbacks, EMF symbioses are hypothesized to reduce local plant diversity by favouring local recruitment of the same host species over recruitment of different host species[1,3,4]. This has been called the “EMF dominance hypothesis”[5]. An alternative “mycorrhizal dominance hypothesis” has also been proposed[5], in which increasing dominance of either type of association (AMF or EMF) decreases local plant diversity. This would occur if both types of symbioses favour con-specific recruitment over heterospecific recruitment. Tests of these hypotheses are uncommon and have focused almost exclusively on canopy trees[1,3,4], despite the vast majority of plant diversity in forests being in the understory.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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Same venueOpen Science FrameworkFrench-language works237,207