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Benthos from Baffin Bay Area: a photo catalogue

2018· preprint· en· W2791034649 on OpenAlexaff
Cindy Grant, Laure de Montety, Lisa Tréau de Coeli, Nanette Hammeken, Philippe Archambault, Martin E. Blicher

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBenthosBenthic zoneBayArcticFisheryInvertebrateOceanographyBiodiversityGeographyThe arcticEnvironmental scienceEcologyBiologyGeology

Abstract

fetched live from OpenAlex

Many teams studying benthic biodiversity have faced the challenge of identifying collected specimens while they are at sea. The use of pictures is an efficient way to increase samples processing, while limiting wrong or incorrect identifications that can be done when many people are working on the same project at different times. This catalogue presents a non-exhaustive inventory of more than 750 taxa, most of them named to the species level, of benthic invertebrates recorded in Baffin Bay (Arctic) with a special attention paid to species recorded along the Southwest Greenland coast. It is designed to be an accurate tool for biologists to identify benthic invertebrates occurring in trawl/dredge samples, with the objective to decrease number of preserved samples and time spent on post-survey sample processing. It has proven particularly useful during the implementation of benthos monitoring on national fisheries assessment surveys as recently recommended by CAFF-CBMP (CAFF 2017) as a way to increase our knowledge of long-term and large-scale trends in Arctic benthos communities. The catalogue proposes original photos and drawings. A must for biologist studying benthos from Arctic waters!

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)0.000
metaresearch head score (Gemma)0.001
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 score0.916
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0100.007
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0660.036

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 head0.059
GPT teacher head0.238
Teacher spread0.179 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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