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Additional file 1 of Transient cognitive impairment in the acute phase of stroke – prevalence, risk factors and influence on long-term prognosis in population of patients with stroke (research study – part of the PROPOLIS study)

2023· article· en· W6920790738 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2023
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDeliriumCognitive impairmentMontreal Cognitive AssessmentCognitionTransient (computer programming)Stroke (engine)

Abstract

fetched live from OpenAlex

Additional file 1: Table S1. Comparison of patients with transient cognitive impairment (CI), stable MoCA score and cognitively impaired. Table S2. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively stable’ patients on three-month prognosis. Patients with delirium are excluded from the analysis. Table S3. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively impaired’ patients on three-month prognosis. Patients with delirium are excluded from the analysis. Table S4. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively stable’ patients on one-year prognosis. Patients with delirium are excluded from the analysis. Table S5. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively impaired’ patients on one-year prognosis. Patients with delirium are excluded from the analysis. Table S6. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively stable’ patients on three-month prognosis. Only patients with first MoCA score ≥ 24 are included. Table S7. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively impaired’ patients on three-month prognosis. Only patients with first MoCA score ≥ 24 are included. Table S8. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively stable’ patients on one-year prognosis. Only patients with first MoCA score ≥ 24 are included. Table S9. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively impaired’ patients on one-year prognosis. Only patients with first MoCA score ≥ 24 are included. Table S10. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively stable’ patients on three-month prognosis. Only patients with first MoCA score < 23 are included. Table S11. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively impaired’ patients on three-month prognosis. Only patients with first MoCA score < 23 are included. Table S12. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively stable’ patients on one-year prognosis. Only patients with first MoCA score < 23 are included. Table S13. Influence of post-stroke transient cognitive impairment (CI) compared to ‘cognitively impaired’ patients on one-year prognosis. Only patients with first MoCA score < 23 are included.

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)0.002
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.724
Threshold uncertainty score0.393

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.027
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.7240.058

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 head0.043
GPT teacher head0.344
Teacher spread0.302 · 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.

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
Published2023
Admission routes1
Has abstractyes

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