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Record W2110556391 · doi:10.1139/g00-075

A genetic map of cucumber composed of RAPDs, RFLPs, AFLPs, and loci conditioning resistance to papaya ringspot and zucchini yellow mosaic viruses

2000· article· en· W2110556391 on OpenAlexvenueno aff
Young Hoon Park, Suat Şensoy, Crispin Wye, Rudie Antonise, J. Peleman, Michael J. Havey

Bibliographic record

VenueGenome · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyZucchini yellow mosaic virusRestriction fragment length polymorphismCucumisAmplified fragment length polymorphismPapaya ringspot virusGeneticsPotyvirusCucumber mosaic virusGenetic linkageGenetic markerVirologyVirusPlant virusBotanyGenotypeGenePopulationGenetic diversity

Abstract

fetched live from OpenAlex

The watermelon strain of papaya ringspot virus (PRSV-W) and zucchini yellow mosaic virus (ZYMV) are potyviruses that cause significant disease losses in cucumber. Resistances have been identified primarily in exotic germplasm that require transfer to elite cultivated backgrounds. To select more efficiently for virus resistances, we identified molecular markers tightly linked to PRSV-W and ZYMV resistances in cucumber. We generated F6 recombinant inbred lines (RILs) from a cross between Cucumis sativus L. 'Straight 8' and a line from 'Taichung Mou Gua', TMG1 (susceptible and resistant, respectively, to both viruses), and studied the segregations of amplified fragment length polymorphism (AFLP) markers, randomly amplified polymorphic DNAs (RAPDs), restriction fragment length polymorphisms (RFLPs), and resistances to PRSV-W and ZYMV. A 353-point map of cucumber was generated, delineating 12 linkage groups at LOD 3.5. Linkage arrangements among RFLPs were consistent with previously published maps; however linkages among RAPDs in our map did not agree with a previously published map. Resistances to PRSV-W and ZYMV were tightly linked (2.2 cM) and mapped to the end of one linkage group. One AFLP cosegregated with resistance to ZYMV.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.237
Teacher spread0.217 · 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 designBench or experimental
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

Citations68
Published2000
Admission routes1
Has abstractyes

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