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Record W2339175357 · doi:10.2135/cropsci2015.12.0740

Reinventing Potato as a Diploid Inbred Line–Based Crop

2016· article· en· W2339175357 on OpenAlexaff
Shelley Jansky, Amy O. Charkowski, David S. Douches, Gabe Gusmini, Craig Richael, Paul C. Bethke, David M. Spooner, Richard G. Novy, Hielke De Jong, Walter S. De Jong, John Bamberg, Asunta L. Thompson, Benoît Bizimungu, David G. Holm, Chuck Brown, Kathleen G. Haynes, Vidyasagar Sathuvalli, Richard E. Veilleux, J. Creighton Miller, Jiming Jiang

Bibliographic record

VenueCrop Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyOutcrossingSolanum tuberosumCropInbred strainPloidyAgronomyInbreedingBiotechnologyBotanyGeneticsPopulation

Abstract

fetched live from OpenAlex

The third most important food crop worldwide, potato (Solanum tuberosum L.) is a tetraploid outcrossing species propagated from tubers. Breeders have long been challenged by polyploidy, heterozygosity, and asexual reproduction. It has been assumed that tetraploidy is essential for high yield, that the creation of inbred potato is not feasible, and that propagation by seed tubers is ideal. In this paper, we question those assumptions and propose to convert potato into a diploid inbred line–based crop propagated by true seed. Although a conversion of this magnitude is unprecedented, the possible genetic gains from a breeding system based on inbred lines and the seed production benefits from a sexual propagation system are too large to ignore. We call on leaders of public and private organizations to come together to explore the feasibility of this radical and exciting new strategy in potato breeding.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.234
Teacher spread0.211 · 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 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

Citations243
Published2016
Admission routes1
Has abstractyes

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