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Record W3189062499 · doi:10.1080/23802359.2021.1959441

Complete mitochondrial genome of the harmful algal bloom species <i>Pseudo-nitzschia delicatissima</i> (Bacillariophyceae, Bacillariophyta)

2021· article· en· W3189062499 on OpenAlexaff
Ziyan He, Yang Chen, Zongmei Cui, Mengjia Zhang, Yongfang Zhao, Feng Liu, Nansheng Chen

Bibliographic record

VenueMitochondrial DNA Part B · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Toxins and Detection Methods
Canadian institutionsSimon Fraser University
FundersMajor Scientific and Technological Innovation Project of Shandong ProvinceChinese Academy of Sciences
KeywordsDomoic acidBiologyGenomeGenePhylogenetic treeMitochondrial DNARibosomal RNAMitochondrionGeneticsDiatomEvolutionary biologyBotanyToxin

Abstract

fetched live from OpenAlex

Pseudo-nitzschia is an important genus of diatoms with many species capable of inducing harmful algae blooms (HABs) in coastal and oceanic waters, some of which produce the toxin domoic acid (DA), a neurotoxin that causes amnesic shellfish poisoning (ASP). Pseudo-nitzschia delicatissima is a cosmopolitan species that can induce HABs and produce DA. Nevertheless, mitochondrial genome of P. delicatissima has not been revealed. In this study, we determined the complete mitochondrial genome of P. delicatissima for the first time. The circular mitochondrial genome was 42,182 bp in length with GC content of 30.37%. It consisted of 65 genes including 39 protein-coding genes (PCGs), 24 tRNA genes, and two rRNA genes. This mitogenome has a group II intron, located in the cytochrome c oxidase subunit genes (cox1), with orf790 identified inside the intron region. Phylogenetic analysis revealed that P. delicatissima was clustered well with P. multiseries. This analysis is valuable for studying the evolutionary relationships among Pseudo-nitzschia species, and for comparative analysis of P. delicatissima strains.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.001

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 head0.019
GPT teacher head0.226
Teacher spread0.208 · 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 designBench or experimental
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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueMitochondrial DNA Part BSame topicMarine Toxins and Detection MethodsFrench-language works237,207