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Record W2747828035 · doi:10.1177/1545968317724285

Enhancing the Alignment of the Preclinical and Clinical Stroke Recovery Research Pipeline: Consensus-Based Core Recommendations From the Stroke Recovery and Rehabilitation Roundtable Translational Working Group

2017· article· en· W2747828035 on OpenAlexaff
Dale Corbett, S. Thomas Carmichael, Timothy H. Murphy, Theresa A. Jones, Martin E. Schwab, Jukka Jolkkonen, Andrew N. Clarkson, Numa Dancause, Tadeusz Weiloch, Heidi Johansen‐Berg, Michael Nilsson, Louise D. McCullough, Mary T. Joy

Bibliographic record

VenueNeurorehabilitation and neural repair · 2017
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversité de MontréalUniversity of British ColumbiaHeart and Stroke FoundationUniversity of Ottawa
FundersWellcome Trust
KeywordsStroke (engine)Stroke recoveryRehabilitationClinical trialPhysical medicine and rehabilitationMedicineTranslational researchPhysical therapyCore (optical fiber)Acute strokePathologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

Stroke recovery research involves distinct biological and clinical targets compared to the study of acute stroke. Guidelines are proposed for the pre-clinical modeling of stroke recovery and for the alignment of pre-clinical studies to clinical trials in stroke recovery.

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 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)0.005
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.118
GPT teacher head0.414
Teacher spread0.296 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations88
Published2017
Admission routes1
Has abstractyes

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