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Record W6966832759 · doi:10.5061/dryad.v41ns1s2t

Raw data and Matlab code for: Convergence in carnivorous pitcher plants reveals a mechanism for composite trait evolution

2023· dataset· en· W6966832759 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueExplore Bristol Research · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
FundersNatural Environment Research CouncilRoyal SocietyLeverhulme TrustUK Research and Innovation
KeywordsTraitPhylogenetic treeMechanism (biology)Convergence (economics)Phylogenetic comparative methodsPhylogeneticsConvergent evolutionSupertree

Abstract

fetched live from OpenAlex

Composite traits involve multiple components that, only when combined, gain a new synergistic function. Thus, how they evolve remains a puzzle. We combined field experiments, microscopy, chemical analyses and laser Doppler vibrometry with comparative phylogenetic analyses to show that two carnivorous Nepenthes pitcher plant species convergently evolved identical adaptations in three distinct traits to acquire a new, composite trapping mechanism. Comparative analyses suggest that this new trait arose convergently via ‘spontaneous coincidence’ of the required trait combination, rather than directional selection in the component traits. Our results indicate a plausible mechanism for composite trait evolution and highlight the importance of stochastic phenotypic variation as a facilitator of evolutionary novelty.

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.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.024
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0040.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.005

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 head0.313
GPT teacher head0.447
Teacher spread0.134 · 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

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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