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Record W6886034752 · doi:10.14286/5pgkcf

Apoqnmatulti'k - Bras D'Or Lake

2024· dataset· en· W6886034752 on OpenAlexaffabout

Bibliographic record

VenueOcean Tracking Network · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsOcean Tracking Network
Fundersnot available
KeywordsSituatedHabitatFish <Actinopterygii>Traditional knowledgeTracking (education)Resilience (materials science)

Abstract

fetched live from OpenAlex

This is the OBIS extraction of the Ocean Tracking Network and Dalhousie University (DAL) Apoqnmatulti'k - Bras D'Or Lake, consisting of the release tagging metadata, i.e. the location and date when the tagged animal was released, and summarized detection events of tagged individuals. If readers are interested in the source dataset they may also inquire with the project PIs as listed here or on the OTN web site (https://members.oceantrack.org/project?ccode=BDLSPG). Abstract:Apoqnmatulti'k (Mi'kmaw for we help each other) is a multi-year collaborative research initiative that looks at the health and resilience of fish and other aquatic species in Mi'kma'ki. Guided by Etuaptmumk, or Two-Eyed Seeing, Apoqnmatulti'k pairs Mi'kmaw and local ways of knowing with western scientific methods to co-design and execute tracking programs to document the movements and habitat use of valued species in Pitu'pa'q (Bras d'Or Lake). Project partners include Mi'kmaw rights holders and technical advisors, local knowledge holders, commercial fishers, academia, and government. The project promotes the access, transfer and ownership of knowledge to these communities in support of their decision-making processes. The Bras d'Or Lake is one of two study sites covered under the project. The other is situated in Pekwitapa'qek (Bay of Fundy).

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient 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 score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.184

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 head0.029
GPT teacher head0.293
Teacher spread0.264 · 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; both teacher heads agree on what is shown here.

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

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