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Record W4402348671 · doi:10.37766/inplasy2024.9.0039

Appendectomy and Risk of Parkinson’s Disease: A Systematic Review and Meta-analysis

2024· review· en· W4402348671 on OpenAlexaboutno aff
Hok Leong Chin, Yiu Sing Tsang, Haojun Shi

Bibliographic record

Venuenot available
Typereview
Languageen
FieldSocial Sciences
TopicSocial Policies and Family
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMeta-analysisDiseaseParkinson's diseaseMedicineInternal medicine

Abstract

fetched live from OpenAlex

Embase through September 10, 2024 to identify potential literature. Main outcome(s) Risk of Parkinson's Disease. Quality assessment / Risk of bias analysisThe quality of the collected literature will be assessed using the Newcastle-Ottawa Scale (NOS).Studies with a score >=7 were considered high quality studies.Two researchers will independently conduct the quality assessments.Disagreements will be deferred to a third reviewer for the final decision after discussion. Strategy of data synthesisStatistic analyses of this study will be conducted using Review Manageer 5.4.A random-effects model will be employed.Statistical significance is defined as a p-value 50.Subgroup analysis Subgroup analyses will be conducted, including different subgroups such as sex.Sensitivity analysis Sensitivity analyses will be performed.

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)0.015
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.035
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0170.028
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.103
GPT teacher head0.405
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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
Published2024
Admission routes1
Has abstractyes

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