MétaCan
Menu
← Back to cohort
Record W6943629364 · doi:10.15468/kyhydn

Quantitative PCR (qPCR) of Key Macroalgal Non-Indigenous Species in Nova Scotia and New Brunswick Waters

2024· dataset· en· W6943629364 on OpenAlexaffabout

Bibliographic record

VenueGlobal Biodiversity Information Facility · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsNova scotiaKey (lock)AlgaeEnvironmental DNAFucusBiodiversity

Abstract

fetched live from OpenAlex

To support the surveillance of key macroalgae and non-indigenous species in Nova Scotia and New Brunswick, five quantitative PCR (qPCR) assays were designed and tested at 111 sites in 2022-2023 targeting the following non-indigenous macroalgal species: Antithamnion sparsum, Bonnemaisonia hamifera, Codium fragile, Dasysiphonia japonica, Fucus serratus. All assays were developed in 2022 by the Center for Environmental Genomics Applications (CEGA, Newfoundland, Canada) except Antithamnion sparsum, for which an assay was developed in 2023 by the Aquatic Biotechnology Laboratory (ABL) at the Bedford Institute of Oceanography. All amplification was performed by the ABL in 2022-2023. The assay developed for Fucus serratus was later determined to be non-specific, and amplifies both F. serratus and Fucus distichus.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.243
Threshold uncertainty score0.488

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.008
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.003

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 head0.026
GPT teacher head0.244
Teacher spread0.218 · 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
GenreDataset

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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueGlobal Biodiversity Information Facility→French-language works237,207→