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Record W2030319664 · doi:10.1016/j.gdata.2014.04.005

Microarray-based optimization to detect genomic deletion mutations

2014· article· en· W2030319664 on OpenAlexaff
Eric J. Belfield, Carly Brown, Xiangchao Gan, Caifu Jiang, Dilair Baban, Aziz Mithani, Richard Mott, Jiannis Ragoussis, Nicholas P. Harberd

Bibliographic record

VenueGenomics Data · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsMcGill University
FundersBiotechnology and Biological Sciences Research Council
KeywordsComparative genomic hybridizationBiologyGeneticsArabidopsisMicroarrayGenomeComputational biologyArabidopsis thalianaTiling arrayCopy-number variationDNA microarrayMutantGeneGene expression

Abstract

fetched live from OpenAlex

We performed array comparative genome hybridization (aCGH) analyses of five Arabidopsis thaliana mutants with genomic deletions ranging in size from 4 bp to > 5 kb. We used the Roche NimbleGen Arabidopsis CGH 3 × 720 K whole genome custom tiling array to optimize deletion detection. Details of the microarray design and hybridization data have been deposited at the NCBI GEO repository with accession number GSE55327.

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)0.002
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0080.005

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 head0.027
GPT teacher head0.223
Teacher spread0.196 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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