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Evolutionary changes in leaf and root traits predates changes in mycorrhizal associations in seed plants.

2020· dataset· en· W3085516648 on OpenAlexaff
Oscar J Valverde Barrantes, Hafiz Maherali, Cristopher Baraloto, Christopher B. Blackwood

Bibliographic record

VenueAuthorea · 2020
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiologyBotanyRoot systemDiversification (marketing strategy)HabitPhylogenetic treeAdaptation (eye)Gene

Abstract

fetched live from OpenAlex

Changes in root morphological traits of seed plants has been typically associated with transitions from the ancestral arbuscular mycorrhizal (AM) to the alternative ectomycorrhizal (ECM) or non-mycorrhizal (NM) associations. However, changes in root morphology also coincide with changes in leaf physiology and growth habit during the diversification of Angiosperms. To explore the evolution of root systems and their role in the diversification in seed plants, we assembled a 600+ species database to reconstruct historical changes in root, leaf and growth form in seed plants. Our findings show important shifts in diameter, specific root length and tissue density as Angiosperms diversified. For most plants, changes in morphology occurred before the acquisition of novel mycorrhizal affiliations, but along with changes in leaf hydraulics and growth form. These findings suggest that adaptation in root systems was crucial during plant diversification and defined important ecological divergences among phylogenetic clades.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.008

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 head0.020
GPT teacher head0.230
Teacher spread0.210 · 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 designBench or experimental
Domainnot available
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

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