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Record W3109608130 · doi:10.1093/jas/skaa054.257

69 Connecting with the next generation of shepherds – an online sheep-based webpage serves as an additional tool in Extension education

2020· article· en· W3109608130 on OpenAlexaboutno aff
Braden J Campbell, Jefferson S McCutcheon, F. L. Fluharty, A. J. Parker

Bibliographic record

VenueJournal of Animal Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWeb pageOutreachProduction (economics)Social mediaDescriptive statisticsDisseminationPage viewWorld Wide WebBusinessGeographyComputer scienceWeb developmentPolitical scienceMathematics

Abstract

fetched live from OpenAlex

Abstract Cooperative Extension education continues to maintain a strong foothold in educating people in the agricultural industry. To connect with the next generation of agriculturalists, Extension needs to investigate alternative methods to disseminate educational material. Developing and maintaining a webpage that provides relevant and scientific based sheep production information is critical as interest in the small ruminant industry continues to rise. The Ohio State University Extension Sheep Team webpage provides shepherds across the nation with the latest information regarding sheep production from daily management to industry outreach. In addition, a unique highlight of the webpage includes research summaries of sheep research conducted at Ohio State that are simplified to illustrate real-world application to improve on-farm production efficiencies. Over the past year alone, the OSU Extension Sheep Team webpage has recorded over 90,000 page views with an average visit duration time of approximately two minutes. Of these page views, approximately 9,000 originate from locations beyond the United States including Canada, United Kingdom, Australia, and New Zealand. According to the web servers’ descriptive statistic analysis, the top referral search engine is Google, representing 58% of all page visits. Interestingly, due the OSU Extension Sheep Team’s presence on social media, Facebook accounts for approximately 18% of all page visits whereas direct subscription of the weekly newsletter only accounts for 15% of all page visits. Furthermore, top article topics include those that relate to basic sheep management practices, health and disease, parasite control methods, and common poisonous plants. Due to the unusual weather patterns of 2019, an article related to poisonous plants accounted for 16% of the webpage’s total visits, which surpassed the number of homepage visits. In order to continue providing relevant Extension information, universities should consider utilizing web-based articles to efficiently reach a larger audience and provide timely articles based upon viewer interest.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.181
GPT teacher head0.310
Teacher spread0.130 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2020
Admission routes1
Has abstractyes

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