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Record W2023084754 · doi:10.1089/cpt.2007.9993

Genomic Diversity Research and the Role of Biorepositories

2007· article· en· W2023084754 on OpenAlexaff
Robert Hanner, T. Ryan Gregory

Bibliographic record

VenueCell Preservation Technology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiorepositoryGenotypingGenomeData scienceComputational biologyBiodiversityBiologyBiobankEvolutionary biologyComputer scienceBioinformaticsGeneticsEcologyGeneGenotype

Abstract

fetched live from OpenAlex

Biodiversity repositories underpin the future of research in the life sciences and biotechnology. However, they represent an extremely heterogeneous assemblage of collections that are lacking a comprehensive index of available resources. A set of “best practices” for biospecimen characterization is proposed for repository biomaterials involving standardized species-level molecular genotyping (DNA barcoding) and the quantification of nuclear DNA content (genome size). This approach has implications for upstream sample collection and preservation methods, as well as downstream implications for highlighting biorepository specimens available for genetic and genomic research. The broad application of the approach here proposed will raise the profile of participating biodiversity repositories, facilitate the compilation of validated reference sequences for molecular species recognition, and drive a deeper understanding of the evolution of the genome.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.003
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 head0.017
GPT teacher head0.225
Teacher spread0.208 · 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.

Study designObservational
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

Citations27
Published2007
Admission routes1
Has abstractyes

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