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Record W2747212803 · doi:10.1212/wnl.0000000000004241

Journal Club: Long-term functional outcome in patients with acquired infections after acute spinal cord injury

2017· letter· en· W2747212803 on OpenAlexaff
Freda M. Warner, Bobo Tong, Catherine R. Jutzeler, Jacquelyn J. Cragg, Paulina S. Scheuren, John L. K. Kramer

Bibliographic record

VenueNeurology · 2017
Typeletter
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsInternational Collaboration On Repair Discoveries
Fundersnot available
KeywordsMedicineSpinal cord injurySpinal cordDepression (economics)LesionParalysisPneumoniaImmune systemPopulationSurgeryInternal medicineImmunology

Abstract

fetched live from OpenAlex

Infections, particularly pneumonia, are the primary cause of mortality in individuals with spinal cord injury (SCI).1 Several factors may contribute to the high rate of infections in the SCI population, including motor paralysis and reduced reflexes resulting in aspiration, invasive procedures, and so-called SCI-induced immune depression syndrome (SCI-IDS).2,3 SCI-IDS is thought to occur when the connection between the CNS and the immune system are disrupted by a lesion in the spinal cord, resulting in a decrease in immune function.3 In addition to increased morbidity and mortality, infections after SCI may affect neurologic recovery.2,3 A recent study found that infections impaired the return of muscle strength up to 1 year postinjury; however, the long-term consequences remain uncertain.2

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)0.000
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.045
GPT teacher head0.369
Teacher spread0.324 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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