MétaCan
Menu
Back to cohort
Record W2798153306 · doi:10.1177/1352458518770086

The link between depression and performance on the Symbol Digit Modalities Test: Mechanisms and clinical significance

2018· article· en· W2798153306 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMultiple Sclerosis Journal · 2018
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsPsychologyDepression (economics)Symbol (formal)AudiologyContrast (vision)Cognitive psychologyDevelopmental psychologyMedicineArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the mechanism and clinical significance of depression-related differences in performance on the Symbol Digit Modalities Test (SDMT). METHODS: The influence of depression on two versions of a computerized SDMT (i.e. fixed versus variable code) was assessed. Both versions involve processing speed, but the fixed c-SDMT also encompasses incidental visual memory. RESULTS: Depression was associated with a 19.06% slowing on the variable ( p = 0.002) and an 8.10% slowing on the fixed ( p = 0.219) c-SDMT. CONCLUSION: Depression-associated differences in performance on the SDMT appear linked more to a reduction in processing speed than a decline in incidental visual memory and exceed the 10% threshold considered clinically significant.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.100
GPT teacher head0.278
Teacher spread0.178 · 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