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Record W4394247153 · doi:10.6084/m9.figshare.4012332

DNA Barcoding the Vascular Plant Flora of Southern British Columbia

2016· dataset· en· W4394247153 on OpenAlexaboutno aff
Erin Fenneman, Sean W. Graham

Bibliographic record

VenueFigshare · 2016
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDNA barcodingFlora (microbiology)Vascular plantGeographyBiologyEcologyArchaeologyPaleontologyBacteria

Abstract

fetched live from OpenAlex

Supplementary data for Erin R. Fenneman's MSc Thesis (University of British Columbia), DNA Barcoding the Vascular Plant Flora of Southern BC. Includes sequence data for rbcL and matK DNA barcode markers for 1511 samples, representing 907 vascular plant species. Samples represent both field-collected tissue and UBC herbarium tissue samples. Sequencing was completed by the Canadian Centre for DNA Barcoding (CCDB). Also includes an additional 1286 rbcL and 906 matK sequences downloaded from the Barcode of Life Database (BOLD) and GenBank. Fileset includes Nexus files for sequence alignments, Neighbour Joining trees, Bootstrap Consensus trees, and output files for BLASTn searches using a local custom database.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.137
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.024
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0630.025

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 head0.039
GPT teacher head0.200
Teacher spread0.162 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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