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Record W4413765503 · doi:10.53555/aqqz9k87

Histopathological Investigation On Superoxide Dismutase (SOD) Enzyme Activity Of Fresh Water Teleost Fish (Labeo rohita)

2023· article· en· W4413765503 on OpenAlexvenueno aff
Dev Brat Mishra

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldHealth Professions
TopicDiverse Scientific Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLabeoSuperoxide dismutaseFish <Actinopterygii>EnzymeBiologyFisheryChemistryBiochemistry

Abstract

fetched live from OpenAlex

Present paper deals with the investigation of superoxide on the physiological impacts of environmental stressors, namely pollution, on the health of freshwater teleost fish by investigating their histopathological hepatosomatic index (HSI) and superoxide dismutase (SOD) enzyme activity. Bindeshwari Fishery pond in Bhilampur, Jaunpur district, was used to collect fish samples. The fish's liver, kidneys, testicles, and ovaries showed major changes after being exposed to the contaminants, according to histopathological analyses. Normal cellular architecture and well-organized liver structures were hallmarks of the healthy histological findings seen in the control group. Atrazine, contaf, and fenvalerate, on the other hand, caused oxidative stress symptoms in fish, such as inflammation, cellular necrosis, and structural alterations in hepatocytes, which were associated with elevated SOD activity. These results point to a physiological reaction to environmental pollutants that cause oxidative damage.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.486
GPT teacher head0.413
Teacher spread0.073 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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