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External validation of the SI2NCAL2C score for outcomes following cerebral venous thrombosis

2024· article· en· W4394796314 on OpenAlexaff
Piers Klein, Liqi Shu, Erik Lindgren, Maria A. de Winter, James E. Siegler, Alexis N. Simpkins, Satareh Salehi Omran, Mirjam R. Heldner, Adam de Havenon, Mohamad Abdalkader, Sami Al Kasab, Christoph Stretz, Teddy Y. Wu, Duncan Wilson, Syed Daniyal Asad, Eyad Almallouhi, Jennifer Frontera, Lindsey Kuohn, Aaron Rothstein, Ekaterina Bakradze, Nils Henninger, Adeel Zubair, Richa Sharma, Deborah Kerrigan, Yasmin Aziz, Eva Mistry, Mayte Sánchez van Kammen, Turgut Tatlisumak, Katarzyna Krzywicka, Diana Aguiar de Sousa, Katarina Jood, Thalia S. Field, Shadi Yaghi, Jonathan M. Coutinho, Thanh N. Nguyen

Bibliographic record

VenueJournal of Stroke and Cerebrovascular Diseases · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleIntracerebral hemorrhageReceiver operating characteristicVenous thrombosisCohortModified Rankin ScaleLogistic regressionNomogramInternal medicineThrombosisSurgeryIschemic stroke

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.020
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.041
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.278
Teacher spread0.260 · 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 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

Citations6
Published2024
Admission routes1
Has abstractno

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