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Record W4362674864 · doi:10.1212/wnl.0000000000207226

Reader Response: Effect of Cholinesterase Inhibitors on Mortality in Patients With Dementia: A Systematic Review of Randomized and Nonrandomized Trials

2023· review· en· W4362674864 on OpenAlexaff
Jennifer Watt, Areti-Angeliki Veroniki, Zahra Goodarzi, Sharon E. Straus

Bibliographic record

VenueNeurology · 2023
Typereview
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsSystems, Applications & Products in Data Processing (Canada)
Fundersnot available
KeywordsDementiaRandomized controlled trialMeta-analysisMedicineSystematic reviewCholinesteraseMEDLINEClinical trialIntensive care medicinePsychologyInternal medicineDisease

Abstract

fetched live from OpenAlex

We read this systematic review and meta-analysis with interest.1 Given the importance of this clinical topic, we have several questions and points of clarification for authors on their review conduct.1. How was the literature search strategy developed?In a systematic review and meta-analysis that we published, which included a comparison of mortality risk in patients with dementia

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)0.037
metaresearch head score (Gemma)0.219
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.219
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0030.004
Science and technology studies0.0020.002
Scholarly communication0.0050.006
Open science0.0040.004
Research integrity0.0230.022
Insufficient payload (model declined to judge)0.0240.009

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 head0.059
GPT teacher head0.366
Teacher spread0.308 · 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 designSystematic review
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

Citations0
Published2023
Admission routes1
Has abstractyes

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