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Record W2013279489 · doi:10.2298/abs1203085i

Activity of gypsy moth dorsolateral neurosecretory neurons under increased rearing density

2012· article· en· W2013279489 on OpenAlexaff
Larisa Ilijin, Milena Vlahović, Marija Mrdaković, Jelica Lazarević, Dragana Matić, Vera Nenadović, Vesna Perić‐Mataruga

Bibliographic record

VenueArchives of Biological Sciences · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsInstitute for Biological Sciences
FundersMinistarstvo Prosvete, Nauke i Tehnološkog Razvoja
KeywordsLymantria disparGypsy mothLarvaPetri dishInstarBiologyAnatomyAnimal scienceZoologyBotanyMicrobiology

Abstract

fetched live from OpenAlex

Lymantria dispar caterpillars were reared under two different rearing densities for the first three days of the 4th larval instar: 5 larvae that were kept in a Petri dish (V = 80 ml) belonged to the intense stress (D1 group); 5 larvae that were kept in a plastic cup (V = 300ml) belonged to the group exposed to less intense stress (D2 group). In the control group, single larvae were reared in a Petri dish. Morphometric changes in L1, L2 and L2? dorsolateral neurosecretory neurons (nsn) were analyzed. After keeping 5 larvae in a Petri dish, the size of L2 neurosecretory neurons (nsn) significantly increased. Rearing 5 larvae in a plastic cup significantly increased the size of L1 nsn nuclei and the number of L2?nsn. A decrease in relative band densities in the region of molecular masses (11-15 kD) that correspond to prothoracicotropic hormones in the gypsy moth was observed in the electrophoretic profiles that were obtained after both treatments in comparison to the control group.

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 score0.002
Threshold uncertainty score0.003

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 studies0.0000.000
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 head0.097
GPT teacher head0.322
Teacher spread0.224 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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