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Record W1990339994 · doi:10.1159/000056984

The combination of SKY and specific loci detection with FISH or immunostaining

2001· article· en· W1990339994 on OpenAlexaff
C.J. Ye, Wenhan Lu, G. Liu, S.W. Bremer, Y.A. Wang, Pierre Moens, Mark Hughes, Stephen A. Krawetz, Henry H. Heng

Bibliographic record

VenueCytogenetic and Genome Research · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsYork University
Fundersnot available
KeywordsBiologyKaryotypeGenomeChromosomeFish <Actinopterygii>SkyComputational biologyGeneticsImmunostainingGeneEvolutionary biologyFishery

Abstract

fetched live from OpenAlex

Spectral karyotyping (SKY) represents an effective tool to detect individual chromosomes and analyze major karyotype abnormalities within an entire genome. We have tested the feasibility of combining SKY and FISH/protein detection in order to combine SKY's unique abilities with specific loci detection. Our experimental results demonstrate that various combined protocols involving SKY, FISH and immunostaining work well when proper procedures are used. This combined approach allows the tracking of key genes or targeted chromosome regions while monitoring changes throughout the whole genome. It is particularly useful when simultaneously monitoring the behavior of both protein complexes and DNA loci within the genome. The details of this methodology are described and systematically tested in this communication.

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)0.003
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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.284
Teacher spread0.252 · 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

Citations28
Published2001
Admission routes1
Has abstractyes

Explore more

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