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Record W2066106916 · doi:10.1080/15538362.2012.679174

Evaluation of Mulch Types on Growth and Development of Native Wild Roses (<i>Rosa</i>spp.) for Rose Hip Production in Prince Edward Island, Canada

2012· article· en· W2066106916 on OpenAlex
Kevin Sanderson, Sherry Fillmore

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Fruit Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsMulchStrawHorticultureSawdustAgricultureAgronomyYield (engineering)BiologyAgroforestryGeographyEcology

Abstract

fetched live from OpenAlex

This study was carried out to assess the impact of five different mulch types (straw, bark, woodchips, sawdust, and black plastic) on growth and yield of domestically cultivated native wild roses (Rosa spp.) in Prince Edward Island, Canada. The experiment was carried out at the Agriculture and Agri-Food Canada, Crops and Livestock Research Centre, Harrington Research Farm in Harrington, Prince Edward Island from 2005–2009. A replicated trial was set up with each plot divided equally into hand-weeded and non-weeded treatments. Straw mulch proved to be a practical choice for commercial producers as it was conducive to plant growth—with greater height, spread, and rose hip yield—as well as being inexpensive and easily obtainable. Black plastic mulch also supported good plant growth and production as well as being easy to maintain. Generally, hand-weeding in combination with mulching was most effective in establishing healthy, productive wild rose plantations.

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)0.002
metaresearch head score (Gemma)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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)0.0000.000

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 head0.059
GPT teacher head0.330
Teacher spread0.271 · 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