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Record W7101624164 · doi:10.21966/vdyq-r660

Environmental DNA survey of Calvert Island, British Columbia, 2021

2021· dataset· W7101624164 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHakai Institute · 2021
Typedataset
Language
FieldComputer Science
TopicCybersecurity and Information Systems
Canadian institutionsFisheries and Oceans CanadaMcGill University
Fundersnot available
KeywordsEnvironmental DNABiodiversityHabitatInvertebrateFish <Actinopterygii>Marine habitatsBenthic habitatFishingDNA sequencing

Abstract

fetched live from OpenAlex

This data package contains molecular resources derived from a large DNA-based survey of marine biodiversity carried out around Calvert Island, British Columbia, in 2021. During this survey we collected triplicate seawater samples from 208 sites across a marine region roughly 100km2 in scale, focussed on nearshore habitats of kelp, seagrass, and rocky reefs. All samples were collected adjacent to the substrate using a niskin bottle, filtered using 0.22μm sterivex filters, and the resulting environmental DNA was used for amplicon sequencing to infer the communities of fish (12S rRNA gene) and invertebrates (COI) at each location. These data are part of a larger collaboration between researchers from McGill University, Fisheries and Oceans Canada, and the Hakai Institute, with the goal of optimizing the use of environmental DNA for monitoring Canada’s network of Marine Protected Areas.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.367
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.216
Teacher spread0.199 · 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