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Record W1850328361 · doi:10.6000/1927-5129.2015.11.65

Effect of Different Diets on The Development and Morphometric of Coccinella septempunctata (Linneous)

2015· article· en· W1850328361 on OpenAlexvenueno aff
Aslam Bukero, Mushtaque Ahmed Nizamani, Imtiaz Ahmed Nizamani, Syed Shahzad Ali, Muhammad Ibrahim Khaskheli, Abdul Ghani Lanjar, Manzoor Ahmed Abro, Shahzad Ali Nahiyoon

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
Fundersnot available
KeywordsFecundityAphidPupaBiologyInstarCoccinella septempunctataLarvaAnimal scienceHorticultureBotanyToxicologyPredationEcologyPredatorCoccinellidaePopulation

Abstract

fetched live from OpenAlex

A laboratory experiment was carried out to determine the effect of different diets on biology of Coccinella septemputata Linneous, in the | department of Plant protection, Sindh Agriculture University, Tando Jam, Pakistanduring 2011 and 2012 at 28±2 ºC and 65±5% relative humidity. The result showed that total larval developmental period was recorded 8.0 ± 0.72 and 7.8 ± 0.69 days on grain moth eggs and safflower aphid, respectively, however, no significant difference was recorded between pre-pupal and pupal period on grain moth egg and safflower aphid. The adult longevity of male (43.10 ± 1.04 and 56.50 ± 1.61) and female (36.07 ± 0.24 and 42.50 ± 0.69 days) was significantly different on grain moth eggs and safflower aphid, respectively. The larval instars were not survived on prepared artificial diet, however, only adult male and female survived (68.50 ± 2.03 and 72.90 ± 2.07 days) without fecundity. The result further revealed that the length and breadth (mm) of larval instars, pupa and adults of C. septempuntata was significantly varied feeding on grain moth eggs and safflower aphid.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.139

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.236
Teacher spread0.197 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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