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Record W4390974259 · doi:10.3389/fhort.2023.1268970

Unlocking heirloom diversity: a pathway to bridging global challenges in modern apple cultivation

2024· article· en· W4390974259 on OpenAlexafffund
Mirella Aoun

Bibliographic record

VenueFrontiers in Horticulture · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsBishop's University
FundersBishop's UniversityAmerican University of Beirut
KeywordsAgricultureBiodiversityGenetic diversityAgricultural biodiversityAgroforestryClimate changeGeographyCultivarGenetic resourcesBiologyEcologyEnvironmental resource managementEnvironmental scienceBiotechnologyAgronomy

Abstract

fetched live from OpenAlex

Reports indicate that climate changes will result in the extinction of a significant percentage of plant species even though many of these species contributed to crucial genetic traits that led to the development of domestic crops. In the past, the diversified range of plant species, varieties, and agricultural practices allowed agriculture production and local food systems to tolerate moderate climate variability. Today, industrial farming relies on very limited genetic diversity for commercial production. Narrowing the genetic base leads to higher susceptibility to environmental changes and diseases. Heirloom cultivars survived climate variations and extreme conditions but were abandoned in favor of a handful of commercial cultivars that dominate the food industry and fit the standards of the global food system. From a climate change perspective, it would be important to conserve heirloom cultivars to preserve biodiversity and make greater genetic diversity available to farming, which will lead to resilience and adaptation.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0040.005
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.045
GPT teacher head0.261
Teacher spread0.215 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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