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Record W2377879377

Value of Cog-12 in predicting cognitive impairment in the elderly

2015· article· en· W2377879377 on OpenAlex
Pan Xiao-don

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueZhonghua laonian xin-nao-xueguanbing zazhi · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCogMontreal Cognitive AssessmentMedicineCognitionCognitive impairmentDementiaInternal medicineArea under the curveAudiologyPsychiatryDisease
DOInot available

Abstract

fetched live from OpenAlex

Objective To study the value of Cog-12 in predicting cognitive impairment in the elderly.Methods At the beginning,56 individuals were enrolled into this study including mild cognitive impairment(MCI)patients and normal cognitive function individuals-involving a control group(n=18),11 patients with normal cognitive function who converted to MCI patients served as a CM group,10 MCI patients with their MCI maintaining stable during the 2-years follow-up period served as MM group,11 MCI patients who converted to AD patients served as an AD group.The patients were scored according to Cog-12,MoCA and MMSE,and their cognitive function was assessed at admission and after two years of follow-up.Results The MoCA and MMSE scores were significantly higher whereas the Cog-12-Ⅰscore was significantly lower in control group than in CM group(P0.05).The MoCA score was significantly higher whereas the total Cog-12-Ⅰand Cog-12 scores were significantly lower in MM group than in AD group(P0.05).The Cog-12 score was a predicting factor for MCI in patients with normal cognitive function(P=0.029).The area under ROC curve showed that the sensitivity of Cog-12 score in predicting MCI was 81.4% when its cutoff value was 4.5.Conclusion Cog-12 is an effective tool for assessing the intelligence,mental state and behaviors of cognitive impairment patients and can thus predict their cognitive impairment.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.289
Teacher spread0.235 · 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