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Record W2792232361

The effect of Myriophyllum aquaticum on freshwater bodies in British Columbia

2018· article· en· W2792232361 on OpenAlexaboutno aff
Rosalyn Desa, Shirvin Lee

Bibliographic record

VenueExpedition · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsMyriophyllumAquatic plantBotanyEcologyBiologyMacrophyte
DOInot available

Abstract

fetched live from OpenAlex

Myriophyllum aquaticum is an invasive plant species originating from the Amazon River and is currently found in British Columbia. We hypothesized that freshwater sources with Myriophyllum aquaticum would have lower dissolved oxygen content compared to areas without Myriophyllum aquaticum . During this experiment, 40 water samples were collected from each of our four sites: Serpentine Fen (Surrey, B.C.), Nicomekl River (Surrey, B.C.), Alpine Garden Pond and Meyer Glade at the University of British Columbia Botanical Garden (Vancouver, B.C.). Serpentine Fen had Myriophyllum aquaticum while the other three sites were control sites. The dissolved oxygen content (mg/L) was measured with an oxygen meter and recorded for comparison. When comparing the data from Serpentine Fen to Nicomekl River, Alpine Garden Pond and Meyer Glade, a paired t-test was used. P-values of 2.2753E-22, 1.082E-29 and 9.0394E-29 were obtained for these sites. Since they are all less than 0.05, the null hypothesis was rejected and support was provided for the alternate hypothesis that Myriophyllum aquaticum decreases the dissolved oxygen content in freshwater bodies. The results also suggest that a decrease in temperature may increase the dissolved oxygen content because numerous biota cannot survive the colder temperatures, thus less oxygen is being used.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.519

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.003
GPT teacher head0.200
Teacher spread0.197 · 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 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
Published2018
Admission routes1
Has abstractyes

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