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Record W2946267064 · doi:10.1016/j.ynstr.2019.100171

Stress and glucocorticoid modulation of feeding and metabolism

2019· review· en· W2946267064 on OpenAlexafffundabout
Georgia Balsevich, Alfonso Abizaid, A. Chen, Ilia N. Karatsoreos, Mathias V. Schmidt

Bibliographic record

VenueNeurobiology of Stress · 2019
Typereview
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsCarleton UniversityUniversity of Calgary
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on AgingBayerisches Staatsministerium für Wirtschaft, Infrastruktur, Verkehr und TechnologieBundesministerium für Bildung und ForschungCanadian Institutes of Health ResearchJoint Programming Initiative A healthy diet for a healthy lifeNational Science Foundation
KeywordsPerspective (graphical)Context (archaeology)GlucocorticoidStress (linguistics)NeurosciencePsychologyCognitive scienceBiologyComputer scienceEndocrinology

Abstract

fetched live from OpenAlex

This perspective highlights research presented as part of the symposium entitled, "Stress and Glucocorticoid Modulation of Feeding and Metabolism" at the 2018 Neurobiology of Stress Workshop held in Banff, AB, Canada. The symposium comprised five researchers at different career stages who each study different aspects of the interaction between the stress response and metabolic control. Their collective results reveal the complexity of this relationship in terms of behavioural and physiological outcomes. Their work emphasizes the need to consider the level of interaction (cellular, tissue, systems) as well as the timing and context in which the interaction is studied. Rather than a comprehensive review on the work presented at the Symposium, here we discuss recurring themes that emerged at the biennial workshop, which address new avenues of research that will drive the field forward.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.065
GPT teacher head0.321
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations15
Published2019
Admission routes3
Has abstractyes

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