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Record W2370805791

GENETIC STRUCTURES OF CHYDORUS SPHAERICUS POPULATIONS FROM LAKE DONGHU, WUHAN

2013· article· en· W2370805791 on OpenAlexaboutno aff
Hu Hong

Bibliographic record

VenueActa Hydrobiologica Sinica · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBacillus sphaericusPopulationSampling (signal processing)BiologyGenetic structureEcologyGenetic variationGeneGeneticsBacillales
DOInot available

Abstract

fetched live from OpenAlex

To estimate the possible influence of the artificial embankments on the genetic structure of Chydorus sphaericus in Lake Donghu, the COⅠgene of C. sphaericus from Lake Donghu, Wuhan, was analyzed with classical DNA sequencing. The results showed that C. sphaericus collected from seven sampling sites at Lake Donghu were not classified into different groups. Both global test and pairwise difference test indicated that there was no remarkable inheritance difference among seven C. sphaericus populations. The N-J tree indicated that COⅠgene of C. sphaericus from Lake Donghu was clustered into one group and those from different regions were clustered into different groups except Lake Kookatsoon, Yukon Territory, which were clustered into the Lake Donghu group. The correlation analysis between pairwise distances of COⅠgene sequences of C. sphaericus and geography distances among sampling sites showed that there were distance-decay relationships regardless within Lake Donghu or in larger scales. This result indicated that there was distribution restriction in C. sphaericus populations. In conclusion, the artificial embankments in Lake Donghu that were built 50 years ago did not cause remarkable influence on the genetic structure of C. sphaericus population in Lake Donghu. The relatively strong passive diffusivity of C. sphaericus in small scales may be one of the reasons that neutralized the influence of the artificial embankments on the population genetic structure.

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 score0.467
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.028
GPT teacher head0.211
Teacher spread0.183 · 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
Published2013
Admission routes1
Has abstractyes

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