MétaCan
Menu
Back to cohort
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 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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.007
Science and technology studies0.0010.007
Scholarly communication0.0020.000
Open science0.0120.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.000

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 head0.011
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 teacher head, not a consensus.

Study designNot applicable
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

Explore more

Same venueOpen Science FrameworkFrench-language works237,207