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Record W2590316748 · doi:10.4141/cjps2011-132

Short communication: Tolerance of Vineland apple rootstocks to waterlogging and <i>Phytophthora</i> infestation

2012· article· en· W2590316748 on OpenAlexaffvenue
C.R. Hampson, Paul M. Randall, P. L. Sholberg

Bibliographic record

VenueCanadian Journal of Plant Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsRootstockBiologyPhytophthoraPhytophthora cactorumHorticultureShootWaterlogging (archaeology)BlightBotanyAgronomyEcologyWetland

Abstract

fetched live from OpenAlex

Hampson, C. R., Randall, P. and Sholberg, P. 2012. Short communication:Tolerance of Vineland apple rootstocks to waterlogging and Phytophthora infestation. Can. J. Plant Sci. 92: 267–269. The Vineland (V) apple (Malus) rootstock series has displayed a range of dwarfing potential and fire blight resistance in research test plots. Knowledge of their resistance to crown and root rot, incited by Phytophthora spp., is desirable before recommending them for on-farm testing, but information on this subject is lacking. Therefore, we tested the response of V.1, V.2, V.3 and V.4 clonal rootstocks to Phytophthora (P. cactorum and P. cryptogea) and waterlogging (0, 24 or 48 h per week for 4 mo) in a factorial greenhouse experiment on potted plants, using M.9 (moderately resistant to Phytophthora) and MM.106 (susceptible) as standards for comparison. Root fresh weight was reduced equally by both pathogens relative to uninoculated controls; rootstocks differed in their response to flooding but not to pathogen treatment. Shoot fresh weight was depressed by flooding in a rootstock- and pathogen-dependent manner. In general, all four V rootstocks had better root and shoot growth than MM.106 in the flooding treatments, and all grew as well as, or better than M.9.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.532

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 head0.032
GPT teacher head0.262
Teacher spread0.230 · 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 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

Citations4
Published2012
Admission routes2
Has abstractyes

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