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Record W2024318179 · doi:10.1080/15538362.2011.619358

Moss Competition Dynamics and Suppression Technologies in Wild Blueberry Production

2012· article· en· W2024318179 on OpenAlex
David Percival, David J. Garbary

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.

Bibliographic record

VenueInternational Journal of Fruit Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsSt. Francis Xavier UniversityNova Scotia Department of Agriculture
Fundersnot available
KeywordsMossCanopyGrowing seasonCompetition (biology)AgronomyBiologyBotanyHorticultureEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

Increasing moss pressures have been observed in wild blueberry fields, which have been attributed to increased precipitation, reliance of fertilizers to provide adequate yield potential, and increasing soil organic matter content. This has coincided with uncertainty regarding the distribution and diversity of mosses present in fields, the competitive nature of selected mosses, and if required, effective suppression technologies. Research conducted from 2006 to 2009 indicated that mosses were present in every sampled field (n = 40), hair cap moss (Polytrichum commune) was the most prevalent moss species observed, and there was no apparent influence of blueberry canopy cover, soil texture, soil pH, or soil moisture on moss incidence. In addition, hair cap moss was observed to physically compete with the wild blueberry for space and remain actively growing late into the autumn and winter. Autumn applications of the herbicide Chateau® (a.i., flumioxazin) were observed to be very effective in suppressing hair cap moss pressures with minimal damage to the wild blueberry, and rapid wild blueberry growth occurred the following growing season.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.080

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.291
Teacher spread0.267 · 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