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О некоторых американских аллюзиях в русской литературе середины XIX века

2007· article· en· W21961831 on OpenAlexfundno aff
Арустамова Анна Альбертовна

Bibliographic record

VenueBulletin of Chelyabinsk State University · 2007
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Experimental evidence suggests an impairment in emotion perception in numerous psychiatric disorders. The results to date are primarily based on research using static displays of emotional facial expressions. However, our natural environment is dynamic and multimodal, comprising input from various communication channels such as facial expressions, emotional prosody, and emotional semantics, to name but a few. Thus, one critical open question is whether alterations in emotion perception in psychiatric populations are confirmed when testing patients in dynamic and multimodal naturalistic settings. Furthermore, the impact task demands may exert on results also needs to be reconsidered. Focusing on schizophrenia and depression, we review evidence on how emotions are perceived from faces and voices in these disorders and examine how experimental task demands, stimulus dynamics, and modality may affect study results.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.023
GPT teacher head0.226
Teacher spread0.203 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2007
Admission routes1
Has abstractyes

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