MétaCan
Menu
Back to cohort

The influences of host plant and genetic resistance to <i>Bacillus thuringiensis</i> on trade‐offs between offspring number and growth rate in cabbage loopers, <i>Trichoplusia ni</i>

2006· article· en· W2086631979 on OpenAlexafffund
Alida F. Janmaat, Judith H. Myers

Bibliographic record

VenueEcological Entomology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsBiologyTrichoplusiaFecundityBacillus thuringiensisHost (biology)OffspringTrade-offPepperBotanyPupaPopulation dynamicsLarvaHorticultureZoologyNoctuidaeEcologyGeneticsDemographyPopulationBacteria

Abstract

fetched live from OpenAlex

Abstract. 1. Variation in progeny size and quality is common among insects and this variation can strongly influence individual fitness. Larger progeny typically survive better and develop faster under adverse conditions and may have higher fecundity. Due to resource limitations, however, trade‐offs may arise between having fewer large offspring or more smaller ones. 2. For cabbage loopers, Trichoplusia ni , pepper leaves are a poorer larval host than cucumber or tomato leaves as indicated by survival, development rate, and body size. Moths reared on cucumber produced more slower growing offspring than those that had been reared on pepper, which produced fewer, faster growing progeny. 3. Traits conferring resistance to Bacillus thuringiensis ( Bt ) generally are associated with strong deleterious effects that may influence resource allocation and reproductive trade‐offs between progeny size and number. 4. Unlike the host‐plant related trade‐off between progeny size and fecundity observed among susceptible control moths, Bt ‐resistant parents had both the lowest fecundity and smallest progeny size on all host plants. This finding suggests that the progeny size–number relationship is constrained in resistant individuals.

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)0.000
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 score0.114
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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

Citations18
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueEcological EntomologySame topicInsect-Plant Interactions and ControlFrench-language works237,207