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Record W6989850907

Clayoquot Sound Harmful Algal Blooms Investigation of Herbert Inlet - 2019

2020· article· en· W6989850907 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Washington Tacoma Digital Commons (University of Washington Tacoma) · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodNektonDiafiltration
DOInot available

Abstract

fetched live from OpenAlex

Clayoquot Sound of British Columbia, Canada is a protected biosphere that has been affected by Alexandrium, a known toxic dinoflagellate, that when consumed by humans can cause paralytic shellfish poisoning. The "BLOB" events that heated the water in the Pacific Ocean in 2014 and 2019 created favorable conditions for these algae to flourish in this region. This study focused on analyzing and comparing nitrate, phosphate, and silicate levels, oceanic conditions, and water properties like temperature, salinity, density, dissolved oxygen, fluorescence, and transmissivity for Herbert Inlet in 2014 and 2019. Surface and bottom samples were collected and sent to the University of Washington School of Oceanography Marine Chemistry Lab for analysis. Meteorological data was collected from Tofino airport, and the tidal data was observed at Riley Cove. A CTD (Conductivity, Temperature, Depth) instrument was used to record the water properties as it was lowered into the water. For the nutrient data, Microsoft Excel was used to create five number summaries, and box and whisker charts. ArcGIS was used to create station maps and choropleth maps that showed the relative abundance of nutrients at each station. Data from the CTD was plotted and showed significant differences from the previous years. The results showed the nutrient levels in 2019 were lower than 2014, but the temperature in 2019 had increased by 2°C throughout the Inlet, and these warmer waters were starting to make their way into the deeper waters throughout Herbert Inlet.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0020.000
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 head0.015
GPT teacher head0.165
Teacher spread0.150 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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