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Record W2970939999 · doi:10.1139/g99-095

Microsatellite repeats are not randomly distributed within Norway spruce (<i>Picea abies </i>K.) expressed sequences

2000· article· en· W2970939999 on OpenAlexvenueno aff
Ivan Scotti, Federica Magni, Ryan C. Fink, W. Powell, Giorgio Binelli, Pete E. Hedley

Bibliographic record

VenueGenome · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
FundersFondazione Lombardia per l'AmbienteNorth Carolina State University
KeywordsMicrosatelliteBiologyPicea abiesDinucleotide RepeatGeneticsPopulationExpressed sequence tagTandem repeatCoding regionComplementary DNAGeneGenomeBotanyAllele

Abstract

fetched live from OpenAlex

A Norway spruce (Picea abies K.) cDNA library obtained from vegetative bud tissue was screened for the presence of (AG) n and (AC) n microsatellite repeats. Ten (AG) n and six (AC) n microsatellites were found, with an average length of 25.5 repeat units. Most of the microsatellites are simple perfect repeats. The microsatellite distribution within the clones is clearly non-random, with different classes of repeats lying in different positions relative to the coding region and in a highly conserved orientation. An estimate of the frequency of dinucleotide microsatellites in expressed regions was obtained, showing that SSRs (simple sequence repeats) are found in genes about 20 times less frequently than in random genomic clones, with (AG) n repeats more frequent than (AC) n repeats. Potential applications of these sequences as expressed region-based molecular markers are shown by developing six SSR markers for the detection of natural variation in Norway spruce populations and testing two of them for the identification of illegitimate progenies from a mapping population. Key words: Picea abies, microsatellites, SSRs, ESTs, population genetics, trees.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.782

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)0.0010.000

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 head0.011
GPT teacher head0.214
Teacher spread0.204 · 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

Citations31
Published2000
Admission routes1
Has abstractyes

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