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Record W2123130824 · doi:10.1098/rspb.2010.2488

Costs of memory: lessons from ‘mini’ brains

2010· review· en· W2123130824 on OpenAlex
James G. Burns, Frédéric Mery

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

VenueProceedings of the Royal Society B Biological Sciences · 2010
Typereview
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer sciencePsychology

Abstract

fetched live from OpenAlex

Variation in learning and memory abilities among closely related species, or even among populations of the same species, has opened research into the relationship between cognition, ecological context and the fitness costs, and benefits of learning and memory. Such research programmes have long been dominated by vertebrate studies and by the assumption of a relationship between cognitive abilities, brain size and metabolic costs. Research on these 'large brained' organisms has provided important insights into the understanding of cognitive functions and their adaptive value. In the present review, we discuss some aspects of the fitness costs of learning and memory by focusing on 'mini-brain' studies. Research on learning and memory in insects has challenged some traditional positions and is pushing the boundaries of our understanding of the evolution of learning and memory.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.727
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0010.001
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 head0.233
GPT teacher head0.382
Teacher spread0.149 · 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