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Record W3042102383 · doi:10.1212/cpj.0000000000000890

Practice Current

2020· article· en· W3042102383 on OpenAlexaff
Aravind Ganesh, Padmaja Genesh, Malik Adil, Malavika Varma, Eric E. Smith

Bibliographic record

VenueNeurology Clinical Practice · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsAlzheimer Society of CanadaUniversity of Calgary
Fundersnot available
KeywordsExpert opinionAudience measurementDementiaMedicineCognitive impairmentCognitionRivastigminePsychologyClinical psychologyPsychiatryIntensive care medicineDiseasePathologyPolitical scienceDonepezil

Abstract

fetched live from OpenAlex

Mild cognitive impairment (MCI) is characterized by evidence of cognitive impairment with minimal disruption of instrumental activities of daily living and carries a substantial risk of progression of dementia. Whereas current guidelines support a relatively minimalistic workup to identify reversible or structural causes, the field has witnessed the rapid development of various sophisticated imaging, biomarker, and genetic investigations in the past few years. The role of these investigations in routine practice is uncertain. Similarly, although there are no approved treatments for MCI, neurologists may experience uncertainty about using cholinesterase inhibitors or other medications or supplements that have been studied in MCI with limited success, particularly when patients or families are keen to try pharmacologic options. Given these uncertainties, and the paucity of high-quality data in the literature, we sought expert opinion from around the globe on how to investigate and treat patients with MCI. Similar questions were posed to the rest of our readership in an online survey, the preliminary results of which are also presented.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.088
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.088
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.003

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 head0.139
GPT teacher head0.519
Teacher spread0.380 · 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 teacher head, not a consensus.

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

Citations3
Published2020
Admission routes1
Has abstractyes

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