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Record W2017707842 · doi:10.1081/pln-100103776

EFFECTS OF THREE ROOTSTOCKS ON PHOTOSYNTHESIS, LEAF MINERAL NUTRITION, AND VEGETATIVE GROWTH OF “BC-2 FUJI” APPLE TREES

2001· article· en· W2017707842 on OpenAlexaffabout
Esmaeil Fallahi, Ik‐Jo Chun, Gerry Neilsen, W. Michael Colt

Bibliographic record

VenueJournal of Plant Nutrition · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsRootstockShootPhotosynthesisBiologyVegetative reproductionMalusHorticultureRosaceaeBotanyAnnual growth cycle of grapevinesAgronomy

Abstract

fetched live from OpenAlex

Net photosynthesis (Pn), leaf nutrition, and current terminal shoot (CTS) growth of ‘BC-2 Fuji’ apple [Malus sylvestris (L.) Mill var.domestica (Borkh.) Mansf.] trees on three rootstocks, Budagovski (Bud.) 9, Ottawa 3, and M.7 EMLA under field conditions were studied in 1998 and 1999. Rootstock affected the scion leaf Pn, leaf mineral concentrations, and vegetative growth. Leaves of trees on Bud.9 had lower Pn than those on the other rootstocks, and the differences were significant in 1999. Scion leaves on Bud.9 had higher calcium (Ca) and manganese (Mn) but lower potassium (K) concentrations than those on the other rootstocks. Leaves of trees on M.7 EMLA had significantly higher magnesium (Mg), K, and copper (Cu) concentrations than those on the other rootstocks in both years. Trees on Ottawa 3 had significantly lower leaf Cu concentrations than those on the other rootstocks during both 1998 and 1999. Trees on Bud.9 rootstock had shorter limbs and terminal shoots than those on the other rootstocks in 1998 and 1999.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.208
Teacher spread0.193 · 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

Citations74
Published2001
Admission routes2
Has abstractyes

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