MétaCan
Menu
Back to cohort
Record W2791588475 · doi:10.1080/19420889.2018.1434390

Green tea and cocoa enhance cognition in<i>Lymnaea</i>

2018· article· en· W2791588475 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCommunicative & Integrative Biology · 2018
Typearticle
Languageen
FieldMedicine
TopicMedicinal Plants and Neuroprotection
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsLymnaeaCognitionLymnaea stagnalisMemory formationFood scienceConditioningBiologyPsychologyChemistryNeuroscienceEcologySnail

Abstract

fetched live from OpenAlex

A flavonoid, (-)-epicatechi (Epi), enhances long-term memory (LTM) formation in Lymnaea and reverses memory obstruction caused by stress. Many foods contain substantial amounts of Epi, (e.g. green tea and cocoa). In humans eating such foods may directly or indirectly enhance cognition. We directly test whether operant conditioning training Lymnaea in these natural foods result in the same effects as training snails in pure Epi. We found that exposure to products containing high concentrations of Epi (e.g. green tea and cocoa) during training enhanced memory formation and could even reverse a learning and memory deficit brought about by stress. Epi can be photo-inactivated by exposure to ultraviolet light. We found that following photo-inactivation of Epi, memory enhancement did not occur. Photo-inactivation of foods containing Epi (e,g. green tea) blocked their ability to enhance LTM. Our data are thus consistent with the hypothesis that dietary sources of Epi can have positive benefits on cognitive ability and be able to reverse memory aversive states.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.431

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 studies0.0000.001
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 head0.036
GPT teacher head0.354
Teacher spread0.318 · 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