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Record W4383069887 · doi:10.1139/cjz-2022-0213

Neuroendocrinology of the vase tunicate, <i>Ciona intestinalis</i>: consideration of the practical applications for the control of this invasive species

2023· article· en· W4383069887 on OpenAlexaffvenue
Sabine R. Lovejoy

Bibliographic record

VenueCanadian Journal of Zoology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCiona intestinalisTunicateBiologyChordatePhylogenetic treeCionaZoologyInvasive speciesSister groupLineage (genetic)EcologyHabitatVertebrateGeneGenetics

Abstract

fetched live from OpenAlex

The vase tunicate, Ciona intestinalis (Linnaeus, 1767), is a social but non-colonial ascidian that is implicated in biofouling of aquatic structures and destruction of the shellfish industry through competition for planktonic nutrients and substrate settling habitats. The sequencing of the C. intestinalis genome has provided insight into the phylogenetic origins of this species, indicating that this lineage and its allies represent a sister taxon to the chordates. Although the practical use of this genomic information at controlling this invasive species is equivocal, a number of new studies on the neurological and neuroendocrine aspects of C. intestinalis have suggested new molecular targets that may be exploited for practical applications on the control of C. intestinalis to protect and enhance the shellfish industry from this invasive species. As a result, we have developed a novel behavioural assay for C. intestinalis, which can be employed to investigate novel agents that inhibit growth and development in this species.

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)0.000
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.242
Teacher spread0.214 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

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