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Record W2960233940 · doi:10.1139/apnm-2018-0738

On the horizon of aging and physical activity research

2019· review· en· W2960233940 on OpenAlexaffvenueabout
Jennifer M. Jakobi, Jerome A. Dempsey, Ylva Hellsten, Richard Monette, Jayne M. Kalmar

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2019
Typereview
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsBanff CentreWilfrid Laurier UniversityUniversity of British Columbia, Okanagan Campus
Fundersnot available
KeywordsPhysical activityGerontologyMedicinePhysical medicine and rehabilitationPsychology

Abstract

fetched live from OpenAlex

This viewpoint is the result of a Horizon Round Table discussion of Exercise and Aging held during the 2017 Saltin International Graduate School in Exercise and Clinical Physiology in Gatineau, Quebec. This expert panel discussed key issues and approaches to future research into aging, across human physiological systems, current societal concerns, and funding approaches. Over the 60-min round table discussion, 3 major themes emerged that the panel considered to be “On the Horizon” of aging research. These themes include (i) aging is a process that extends from womb to tomb; (ii) the importance of longitudinal experimental studies; and (iii) the ongoing need to investigate multiple systems using an integrative approach between scientists, clinicians, and knowledge brokers. With a focus on these themes, we aim to identify critical questions, challenges, and opportunities that face scientists in advancing the understanding of exercise and aging.

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)0.006
metaresearch head score (Gemma)0.005
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 score0.013
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0020.003
Scholarly communication0.0050.007
Open science0.0010.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0050.002

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 head0.162
GPT teacher head0.432
Teacher spread0.270 · 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

Citations2
Published2019
Admission routes3
Has abstractyes

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