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Record W1986772133 · doi:10.1080/15538360802365939

Maritime Provinces Wild Blueberry Fertilizer Study

2008· article· en· W1986772133 on OpenAlexaff
Kevin Sanderson, Leonard J. Eaton, Michel Melanson, Sylvia Wyand, Sherry Fillmore, Chris Jordan

Bibliographic record

VenueInternational Journal of Fruit Science · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsGovernment of New BrunswickNova Scotia Department of AgricultureUniversity of Prince Edward IslandAgriculture and Agri-Food Canada
Fundersnot available
KeywordsFertilizerAmmonium sulfateCropYield (engineering)CroppingAgronomyAmmoniumHorticultureCrop yieldBiologyChemistryAgricultureEcology

Abstract

fetched live from OpenAlex

Field experiments were carried out over a 4-year period (2001–2004) at one commercial site in each of the Maritime Provinces, Prince Edward Island, Nova Scotia, and New Brunswick. The study was designed to determine the effects of applied fertilizer in sprout year only and in both sprout and crop year on leaf and soil concentration, plant development, and yield. Individually, sprout-year applications of fertilizers ammonium sulfate, di-ammonium sulfate, and 17-17-17 and crop-year application of ammonium sulfate did not affect soil and leaf concentrations, plant growth, or yield. When comparing the mean of fertilizer applications to unfertilized plots, levels of soil, P, K, and S were increased and soil pH decreased and leaf tissue concentrations of N, P, K, and S were increased. Stem length, number of live buds, and number of blossoms were increased; however, yield was not affected in the first cropping cycle and was lowered in the second cropping cycle by applications of fertilizers. Crop-year applications of ammonium sulfate provided no benefit to wild blueberry production.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.791

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.302
Teacher spread0.255 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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