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Record W2274519712 · doi:10.7773/cm.v17i2.803

Effect of season, sex and reproduction on zinc concentration in the soft tissues of Meretrix casta (Chemnitz) (Mollusca: Bivalvia) collected from Vellar Estuary, Porto Novo, India

2017· article· en· W2274519712 on OpenAlexaff
A. Rajan, B. Shanthi, M. Kalyani

Bibliographic record

VenueCiencias Marinas · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAdductor musclesEstuaryGonadZincBiologyMolluscaPerna viridisBivalviaCarangidaeFisheryAnimal scienceZoologyAnatomyMusselChemistry

Abstract

fetched live from OpenAlex

The investigation was undertaken to determine the impact of ecological and biological factors on the bio-accumulation of zinc in Meretrix casta collected from Vellar Estuary. The concentration of zinc in water, sediment, whole animal tissues and different soft body parts, such as adductor muscle, foot, mantle, gill, gonad and digestive diverticula of both male and female, were analysed separately. A high concentration of zinc was discernible during the monsoon, whereas it was low during summer. The metal concentration in the sediment was higher than in the water and body tissues. Among the body tissues, gill tissues showed high values followed by the mantle, digestive diverticula, gonad, foot and adductor muscle. A statistical analysis revealed a significant positive correlation between zinc concentration in body tissues and ambient medium. A significant negative relationship was encountered between salinity and zinc concentration in animal body tissues.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.257
Teacher spread0.245 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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