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Record W4392199957 · doi:10.1038/s41598-024-55261-9

Author Correction: Characterizing the profiles of patients with acute concussion versus prolonged post-concussion symptoms in Ontario

2024· erratum· en· W4392199957 on OpenAlexaffabout
Olivia F. T. Scott, Mikaela Bubna, Emily Boyko, Cindy Hunt, Vicki L. Kristman, Judith Gargaro, Mozhgan Khodadadi, Tharshini Chandra, Umme Saika Kabir, Shannon Kenrick-Rochon, Stephanie Cowle, Matthew J. Burke, Karl Zabjek, Anil Dosaj, Asma Mushtaque, Andrew Baker, Mark Bayley, Flora I. Matheson, Ruth Wilcock, Billie-Jo Hardie, Michael D. Cusimano, Shawn Marshall, Robin Green, T. Blaine Hoshizaki, James S. Hutchison, Tom Schweizier, Michael G. Hutchison, J Zych, David Murty, Maria Carmela Tartaglia

Bibliographic record

VenueScientific Reports · 2024
Typeerratum
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsToronto Western HospitalFowler Kennedy Sport Medicine ClinicMental Health Research CanadaHospital for Sick ChildrenUniversity of OttawaParachuteNOSM UniversityPublic Health OntarioToronto Rehabilitation InstituteOntario Stroke NetworkHealth Sciences NorthOccupational Cancer Research CentreOttawa HospitalHealth Sciences CentreUniversity Health NetworkHamilton Health SciencesUniversity of TorontoSunnybrook Health Science CentreSt. Michael's HospitalLakehead University
Fundersnot available
KeywordsConcussionMedicinePhysical medicine and rehabilitationInternal medicineEmergency medicinePoison controlInjury prevention

Abstract

fetched live from OpenAlex

“The original, de-identified data (including study protocol and data dictionaries) will be available through Brain-CODE ( www.braincode.ca ). Requests to access these datasets should be directed to info@braininstitute.ca.”

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)0.133
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: Other · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.133
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.005
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.1200.042

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 head0.029
GPT teacher head0.301
Teacher spread0.272 · 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
GenreOther

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
Published2024
Admission routes2
Has abstractyes

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