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Record W7038377445

Impact of Cyanobacteria on the pelagic phosphorus cycle

2022· article· en· W7038377445 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks@BGSU (Bowling Green State University) · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSubterranean biodiversity and taxonomy
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodDiafiltrationTSG101HyporeflexiaArticular cartilage damageProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

Research concerning cyanobacteria has increasingly focused on the health implications and causal factors promoting cyanobacterial blooms. However, there is another important aspect of cyanobacterial blooms that have received less attention. Recent studies have provided indirect evidence that pelagic food web function is affected when cyanobacteria are abundant in lakes. This may be due to a combination of factors, such as their inedibility, poor food quality, or their production of cyanotoxins. With the use of a radiotracer, we measured pelagic phosphorus cycling in a variety of lakes from the Canadian Prairie Region and beyond (i.e., Lake Erie and Lake of the Woods). These lakes provided a broad range in cyanobacterial biomass (0 to 75% cyanobacterial biomass). Phosphate turnover, planktonic regeneration, and most important, planktonic food web turnover will be presented as a function of cyanobacterial biomass to determine if food webs dominated by cyanobacteria do indeed have reduced cycling efficiencies.

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 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 score0.056
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.026
GPT teacher head0.184
Teacher spread0.158 · 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
Published2022
Admission routes1
Has abstractyes

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