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Record W3210457041 · doi:10.1111/pre.12470

Diatom (Bacillariophyceae) assemblages in tidal environments of Vancouver Island, British Columbia, Canada

2021· article· en· W3210457041 on OpenAlexaffabout
Yuki Sawai, Koichiro Tanigawa, Tetsuya Shinozaki, Peter Bobrowsky, David Huntley, James Goff

Bibliographic record

VenuePhycological Research · 2021
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsDiatomTransectDetrended correspondence analysisIntertidal zoneOrdinationEcologySpecies richnessBiologySalt marshAbundance (ecology)OceanographyGeology

Abstract

fetched live from OpenAlex

SUMMARY To understand distributions of coastal diatoms along Vancouver Island, British Columbia, Canada, this paper describes diatom assemblages observed in 47 surface sediment samples from intertidal environments. One hundred and eighty‐four diatom taxa were identified from five transects crossing tidal flats, salt marshes, and freshwater forests in Tofino, Ucluelet, and Port Alberni. Distributions of the diatom assemblages were consistent with those reported elsewhere in the Pacific Northwest, but a few diatom taxa show different trends in their distributions. For example, one benthic species Denticula subtilis shows widespread distributions along the transect in Tofino. An ordination shown by Detrended Correspondence Analysis (DCA) using a combined dataset indicated overlapped scatter plots of diatom assemblages, suggesting that assemblages with similar species compositions are observed in more than one location. Hierarchical and k‐means clustering analyses using Euclidean distance recognized unique small groups along each transect. Rank abundance curves show different trends for richness and evenness of diatom assemblages among the five transects.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.033
GPT teacher head0.302
Teacher spread0.269 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

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