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Record W2727436151 · doi:10.1093/geroni/igx004.3665

CAN WE SEE GAIT AND COGNITION RELATIONSHIP AS AN EMERGING GERIATRIC SYNDROME? A ROUNDTABLE DEBATE

2017· article· en· W2727436151 on OpenAlexaff
Matteo Cesari, Manuel Montero‐Odasso, Emanuele Marzetti, Michele L. Callisaya, Jeffrey M. Hausdorff, Caterina Rosano, Joe Verghese

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsWestern University
Fundersnot available
KeywordsCognitionGaitConstruct (python library)PsychologyDiseasePhysical medicine and rehabilitationCognitive psychologyMedicineNeuroscienceComputer sciencePathology

Abstract

fetched live from OpenAlex

A roundtable discussion and debate will summarize the evidence in favor of and against considering “gait and cognition” as an emerging geriatric syndrome. Specifically, we will discuss whether there is sufficient evidence to support the idea that gait and cognitive impairments among older individuals in the absence of an overt neurological disease represent a distinct phenotype caused by shared mechanisms. Potential clinical applicability of the construct will be discussed.

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)0.052
metaresearch head score (Gemma)0.112
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.052
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.112
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0030.002
Science and technology studies0.0060.020
Scholarly communication0.0110.039
Open science0.0090.010
Research integrity0.0460.064
Insufficient payload (model declined to judge)0.0140.006

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 head0.057
GPT teacher head0.336
Teacher spread0.279 · 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
GenreCommentary

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

Citations0
Published2017
Admission routes1
Has abstractyes

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