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Record W4378627721 · doi:10.1002/ppp3.10391

Fruit in focus: A sampler platter of research

2023· article· en· W4378627721 on OpenAlexafffund
Zoë Migicovsky, Elisabeth J. Forrestel, Emily Warschefsky

Bibliographic record

VenuePlants People Planet · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Diversity and Evolution
Canadian institutionsAcadia University
FundersDalhousie University
KeywordsDiversity (politics)BiologySustainabilityTasteEvolutionary biologyData scienceEcologySociologyAnthropologyComputer science

Abstract

fetched live from OpenAlex

Few plants have captured the imagination and palettes of the world like those which bear edible fruits, providing novel insights into the relationships between plants and people. This special collection of reviews and research highlights the unique challenges and opportunities we face when studying, breeding, and working to conserve these species. The 18 articles included here examine fruiting plants across diverse scales and topics, from the genome to global sustainability, and from fruit morphology to species' geographic distributions, yet they showcase only a fraction of the immense evolutionary, phenotypic, and genomic diversity present in fruit‐bearing plants. Across the special collection, our hope is to not only offer highlights of fruit diversity and importance but also provide a taste of future research in this area. We hope you enjoy the fruits of our labor.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.095
GPT teacher head0.277
Teacher spread0.182 · 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 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

Citations1
Published2023
Admission routes2
Has abstractyes

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