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Record W3197684813 · doi:10.4236/as.2021.129060

Marsh Spot Disease and Its Causal Factor, Manganese Deficiency in Plants: A Historical and Prospective Review

2021· article· en· W3197684813 on OpenAlex
Bosen Jia, Penner Waldo, R. L. Conner, Ismaël Moumen, Nadeem Khan, Xuhua Xia, Anfu Hou, Frank M. You

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAgricultural Sciences · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsUniversity of OttawaAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsEpistasisQuantitative trait locusLeaf spotBiologyGeneCandidate geneGeneticsBotany

Abstract

fetched live from OpenAlex

This review provides an examination of the marsh spot disease in beans and the roles played by its causal factor, manganese (Mn) deficiency. The discovery of the marsh spot disease, its relation with Mn deficiency, and how it can be treated are discussed. Mn serves as a cofactor and a catalyst in various metabolic processes in different cell compartments, such as the oxygen-evolving complex of photosystem II (PSII) or reactive oxygen species scavenging. Some major quantitative trait loci (QTL) and putative candidate genes associated with Mn content in plants, especially in plant seeds, have been identified. Marsh spot disease in cranberry common bean is controlled by several major genes with significant additive and epistatic effects. They provide valuable clues for QTL candidate gene prediction and an improved understanding of the genetic mechanisms responsible for marsh spot resistance in plants.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.234
Teacher spread0.212 · 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