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Record W3029130564 · doi:10.1017/cjn.2020.104

Practical Guidance for Outpatient Spasticity Management During the Coronavirus (COVID-19) Pandemic: Canadian Spasticity COVID-19 Task Force

2020· review· en· W3029130564 on OpenAlexaffvenueabout
Rajiv Reebye, Heather Finlayson, Curtis May, Lalith Satkunam, Theodore Wein, Thomas A. Miller, Chris Boulias, Colleen O’Connell, Anibal Bohorquez, Sean P. Dukelow, Karen Ethans, Farooq Ismail, Waill Khalil, Omar Khan, Philippe Lagnau, Stephen McNeil, Patricia Mills, Geneviève Sirois, Paul Winston

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2020
Typereview
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsUniversité LavalFoothills Medical CentreDalhousie UniversityStan Cassidy FoundationToronto Rehabilitation InstituteWest Park Healthcare CentreWestern UniversityUniversity of TorontoUniversity of CalgarySt Joseph's Health CareUniversity of ManitobaMontreal General HospitalHotel Dieu Shaver Health and Rehabilitation CentreSaskatoon City HospitalUniversity of AlbertaHamilton Regional Laboratory Medicine ProgramUniversity of British ColumbiaGF Strong Rehabilitation CentreMcGill UniversityUniversity of SaskatchewanGlenrose Rehabilitation Hospital
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicSpasticity2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)CoronavirusTask forceMedicineTask (project management)VirologyPhysical medicine and rehabilitationInternal medicinePolitical scienceEngineering

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.952
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0160.006

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 head0.153
GPT teacher head0.403
Teacher spread0.250 · 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

Citations14
Published2020
Admission routes3
Has abstractyes

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