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Record W2946039409 · doi:10.1002/ppp3.34

Resetting the table for people and plants: Botanic gardens and research organizations collaborate to address food and agricultural plant blindness

2019· article· en· W2946039409 on OpenAlexaff
Sarada Krishnan, Tara Moreau, Jeff S. Kuehny, Ari Novy, Stephanie L. Greene, Colin K. Khoury

Bibliographic record

VenuePlants People Planet · 2019
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAgricultureBusinessFood systemsSustainabilityFood securityMarketingPolitical scienceEconomic growthGeographyEconomics

Abstract

fetched live from OpenAlex

Societal Impact Statement Food and agricultural plants are integral to human well‐being. Due to their universal importance, such plants would appear to represent an ideal entryway by which to address plant blindness. However, with limited opportunities for direct contact with agriculture, many people cannot appreciate the flora that feed us every day. We provide examples of informal education initiatives aimed at increasing public awareness and appreciation of food and agricultural plants, made possible through collaborations between botanic gardens, academic institutions, nonprofits, and agricultural research organizations. We hope these examples encourage and inspire organizations to further utilize food and agricultural plants to tackle plant blindness. Summary Of the myriad gifts plants provide to humanity, food is among the most visible, as everyone needs to eat, every single day. Due to their universal importance, food and agricultural plants would appear to represent ideal entryways to address plant blindness. Yet increasing urbanization worldwide and decreasing proportions of the global workforce in agriculture are limiting opportunities for people to have direct, hands‐on experiences with food and agricultural plants outside of retail purchasing, meal preparation, and food consumption. This disconnect is troubling, especially as the challenges to the sustainability of our future food supply necessitate that society, and certainly elected decision‐makers, have the capacity to understand the potential benefits, risks, and tradeoffs inherent to agriculture and its advancing technologies. We outline opportunities to address agricultural plant blindness with emphasis on current complex issues within the food and agriculture sector. We provide examples of fruitful collaborations between botanic gardens, academic institutions, nonprofits, and agricultural research organizations that engage people around these issues.

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)0.016
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0200.006
Scholarly communication0.0130.015
Open science0.0040.030
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.0520.009

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 head0.037
GPT teacher head0.315
Teacher spread0.278 · 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 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

Citations42
Published2019
Admission routes1
Has abstractyes

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