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Record W1995199956 · doi:10.6000/1927-5129.2014.10.48

Seasonal and Spatial Growth Patterns of Shrimps Collected from Some Selected Creeks of Sindh, Pakistan

2014· article· en· W1995199956 on OpenAlexvenueno aff
Faiza Sarwar

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFish Biology and Ecology Studies
Canadian institutionsnot available
FundersWWF-PakistanUniversity of Karachi
KeywordsShrimpFisheryBiologyPenaeusMonsoonDecapodaEcologyCrustaceanGeography

Abstract

fetched live from OpenAlex

Shrimps are very important part of the export economy of Pakistan. They share about 60 % the total exports of the sea food. For the studies of shrimp health, the length-weight studies are critical for the evaluation of the shrimp stocks. In this paper an attempt has been made to explore the Length-weight relationships of the shrimps at the creeks zone of Sindh coast (the study area). Furthermore, the impacts of seasonal change on the growth of shrimps (length and weight treated as parameter) have been evaluated. The main objective of this study is to analyze the seasonal and spatial pattern of growth and condition of the selected shrimp species. For this purpose, three most abundant shrimp species Penaeus indicus, Metapenaeus affinis and Exopalaemon styliferus have been selected out of 30 found at the coastal creeks areas of Sindh, Pakistan from April 2013 to January 2014. Pre and Post-Monsoon seasonal changes were analyzed through Geographic Information Science (GIS) and universally accepted equation for LWRs logW = alogLb were applied on three species selected. It has been found that post-monsoon is the ideal period for shrimp catch for three species. LWRs (growth pattern) found stable in Penaeus indicus and Metapenaeus affinis while predicting an alarming deteriorated situation for Exopalaemon styliferus at creeks zone.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.335
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.011
GPT teacher head0.209
Teacher spread0.198 · 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.

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

Citations1
Published2014
Admission routes1
Has abstractyes

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