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Record W3167084625 · doi:10.1139/as-2020-0037

Temporal change in the molluscan assemblages (bivalves and gastropods) of Frobisher Bay, Nunavut, Canada, over 50 years

2021· article· en· W3167084625 on OpenAlexaffvenueabout
Erin C. Herder, Alec E. Aitken, Evan Edinger

Bibliographic record

VenueArctic Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of SaskatchewanMemorial University of Newfoundland
Fundersnot available
KeywordsBayBenthic zoneArcticOceanographyBenthosEcologyGeographyCommunity structureClimate changeEnvironmental changeEnvironmental sciencePhysical geographyGeologyBiology

Abstract

fetched live from OpenAlex

Long-term studies provide an effective way to assess the ecological impacts of decades-long environmental change in Arctic coastal benthic environments, but are rarely undertaken in the Canadian Arctic. In light of this, historical datasets can be compared with modern samples to examine temporal differences in benthic community structure. Frobisher Bay, Nunavut, provides a unique opportunity to use a historical census to examine the impacts that long-term environmental changes have had on the marine benthos. Between 1967 and 1976, and in 2016, infaunal samples were collected in inner Frobisher Bay and were compared to determine how the molluscan assemblages have changed between the two time periods. Molluscan assemblages in two regions of inner Frobisher Bay (Iqaluit and Cairn Island) were examined to minimize sampling discrepancies between the two time periods. A long-term increase in mean annual air temperature and a decline in the length of the ice cover season were observed. Both regions exhibited some change in sediment composition and quality as well as in molluscan assemblage between the two time periods, and species diversity indices also indicated some change between these time periods. Both the 1967–1976 and 2016 molluscan datasets provide a baseline for future long-term studies in a changing Arctic.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2021
Admission routes3
Has abstractyes

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