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Evolutionary Biology of Insect Learning

2007· review· en· W2117879460 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Entomology · 2007
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiologyInsectSocial learningVariation (astronomy)AggressionEcologyVariety (cybernetics)Evolutionary biologyCognitive psychologyArtificial intelligenceDevelopmental psychologyPsychologyComputer science

Abstract

fetched live from OpenAlex

Learning and memory, defined as the acquisition and retention of neuronal representations of new information, are ubiquitous among insects. Recent research indicates that a variety of insects rely extensively on learning for all major life activities including feeding, predator avoidance, aggression, social interactions, and sexual behavior. There is good evidence that individuals within an insect species exhibit genetically based variation in learning abilities and indirect evidence linking insect learning to fitness. Although insects rely on innate behavior to successfully manage many types of variation and unpredictability, learning may be superior to innate behavior when dealing with features unique to time, place, or individuals. Among insects, social learning , which can promote the rapid spread of novel behaviors, is currently known only from a few well-studied examples in social Hymenoptera. The prevalence and importance of social learning in insects are still unknown. Similarly, we know little about ecological factors that may have promoted enhanced learning abilities in insects, and whether learning has significantly contributed to speciation in insects.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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 head0.121
GPT teacher head0.348
Teacher spread0.227 · 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