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Record W1983097758 · doi:10.3389/fpsyg.2012.00015

Attention, Awareness, and the Perception of Auditory Scenes

2012· article· en· W1983097758 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

VenueFrontiers in Psychology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsBaycrest Hospital
FundersUniversity of Nevada, Las VegasNational Science Foundation
KeywordsPerceptionPsychologyAuditory perceptionCognitive psychologySelective auditory attentionModalitiesCognitionStimulus modalityVisual perceptionNeural correlates of consciousnessSensory systemSelective attentionNeuroscience

Abstract

fetched live from OpenAlex

Auditory perception and cognition entails both low-level and high-level processes, which are likely to interact with each other to create our rich conscious experience of soundscapes. Recent research that we review has revealed numerous influences of high-level factors, such as attention, intention, and prior experience, on conscious auditory perception. And recently, studies have shown that auditory scene analysis tasks can exhibit multistability in a manner very similar to ambiguous visual stimuli, presenting a unique opportunity to study neural correlates of auditory awareness and the extent to which mechanisms of perception are shared across sensory modalities. Research has also led to a growing number of techniques through which auditory perception can be manipulated and even completely suppressed. Such findings have important consequences for our understanding of the mechanisms of perception and also should allow scientists to precisely distinguish the influences of different higher-level influences.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.344

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 studies0.0000.001
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 head0.033
GPT teacher head0.324
Teacher spread0.290 · 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