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Record W2884919645 · doi:10.1055/s-0038-1644952

Current research innovations at the NHP Research Alliance

2018· article· en· W2884919645 on OpenAlexaff
Steven-G Newmaster, Subramanyam Ragupathy

Bibliographic record

VenuePlanta Medica International Open · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsData scienceComputer scienceBiobankBiotechnologyBiologyBioinformatics

Abstract

fetched live from OpenAlex

Food security issues and global loss of biodiversity have resulted in considerable demands for botanical ingredients. This situation is intensified by the world-wide increase of 12 – 15% annually in the consumption of natural products; some products will not be sustainable within the next decade due to key ingredients, which are rare species. Consequently, the adulteration of natural health products (NHPs) is frequently in the news, which concerns consumers and brand owners who seek quality nutritional products. In fact, counterfeiting of products is a significant problem for many industry leaders faced with key uncertainties on how to properly identify botanical ingredients using novel molecular diagnostic tools. The NHP Research Alliance is seeking collaboration with industry, researchers and other NHP stakeholders in assemblage of a reliable, Standard Biological Reference Material (SBRMs) DNA library for natural botanical ingredients. This SBRM DNA library is founded on diagnosable phylogenetic species concepts using decision-based theoretical and probabilistic bioinformatic methods founded on multivariate statistical models. Validation of this library includes a database with taxonomic herbarium vouchers of known provenance, genome scans and is validated using analytical chemistry (NMR) as chemical fingerprints. This combination of genomic and metabalomic tools will enable researchers interested in genomics, metabolomics and proteomics as we move into a modern era of NHP research. Members of the NHP Research Alliance will guide the development of novel molecular diagnostic biotechnology that serves as real-time, on-site, industry QA/QC forensic tools for supply chain verification and validation of authentic species ingredients. We present here a snap shot of current research projects at the NHP Research Alliance including DNA testing of botanical extracts and the use of onsite molecular diagnostic tools for quick screening of target species ingredients and adulterants.

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)0.016
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.248
Threshold uncertainty score0.829

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0100.009
Open science0.0040.008
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.2480.174

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 head0.703
GPT teacher head0.706
Teacher spread0.004 · 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 designNot applicable
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

Citations0
Published2018
Admission routes1
Has abstractyes

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