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Genetic Analysis of a Large-Scale Phaeocystis globosa Bloom Offshore Qingdao, China

2022· article· en· W4293771699 on OpenAlexaff
Huiyin Song, Yiqi Wang, Xiangxiang Ding, Nansheng Chen

Bibliographic record

VenueMicroorganisms · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsSimon Fraser University
FundersPolit National Laboratory for Marine Science and TechnologyChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsBloomHaptophyteBiologyAlgal bloomBayGenetic diversityChinaEcologyOceanographyGeographyPhytoplankton

Abstract

fetched live from OpenAlex

A sudden large-scale bloom event of the haptophyte Phaeocystis globosa that lasted over one month in the winter of 2021 was observed offshore Qingdao, China. This P. globosa bloom event was unusual as it was the first P. globosa bloom recorded in Qingdao offshore. Furthermore, the temperature at which this event occurred was much lower than that of previous P. globosa blooms in China. We hypothesize that the P. globosa strains that drove the development of this bloom offshore Qingdao were genetically unique and have a competitive advantage in the environmental conditions. To test this hypothesis, we analyzed P. globosa genetic diversity and the temporal dynamics of the bloom, using the high-resolution molecular markers pgcp1 and cox1 that we developed recently. The analysis revealed that the genetic compositions of P. globosa offshore Qingdao were rather limited, containing two dominant genotypes and other rare genotypes with low abundance, representing a small portion of the genetic diversities identified in coastal waters in China, and were rather different from the P. globosa genotypes outside of the Jiaozhou Bay before the P. globosa bloom in the winter of 2021. This suggested only certain strains contribute to the development of blooms under certain environmental conditions. The genetic composition may indicate the unusual timing and scale of this P. globosa event.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score0.908

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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0930.000

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 head0.004
GPT teacher head0.208
Teacher spread0.204 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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