Paper year
2024
Detect emerging, bridge-candidate, and undercited papers inside a curated audio-ML corpus, then expose the signals behind every recommendation.
Paper dossier
Review source metadata, abstract, authors, topics, and local similarity context before moving into explanation and ranking views.
Paper year
2024
Citations
0
Authors
2
Topic labels
2
Source readout
Journal of the Audio Engineering Society
jaes
Core corpus
Not available yet
Ranking readout
This block uses the same resolved ranking run as Recommended. Ranks here are materialized paper_scores ranks; live Emerging may be reordered by the bounded ML scorer. Family rank is global within each family, but rank is only shown when this paper lands inside the surfaced top 50.
Families present
3
Top 50
0
Run label
shadow-generalization-product-candidate-ranking-v1
Snapshot
source-snapshot-shadow-generalization-v1-20260521
Scope: family global | run rank-83787b91ef
Emerging
Present in run, outside top 50
Emerging: embedding slice fit vs included-corpus centroid (title+abstract), plus citation velocity and topic growth; not universal relevance. Bridge signal not used here.
Signals: semantic=0.8039, citation_velocity=0.0000, topic_growth=0.4167, diversity_penalty=0.0000
Embedding slice fit (corpus centroid): high; used in final ranking (contribution to score: 0.1608)
Recent attention: low; used in final ranking (contribution to score: 0.0000)
Topic momentum: medium; used in final ranking (contribution to score: 0.1250)
Cross-cluster signal: not computed for this run
Similarity penalty: reduces score when non-zero (contribution to score: 0.0000)
Bridge
Present in run, outside top 50
Multi-topic paper in active topics; no cluster_version on this run so bridge_score was not computed.
Signals: citation_velocity=0.0000, topic_growth=0.4167, diversity_penalty=0.3333
Semantic match: not computed for this run
Recent attention: low; used in final ranking (contribution to score: 0.0000)
Topic momentum: medium; used in final ranking (contribution to score: 0.2708)
Cross-cluster signal: not computed for this run
Topic breadth penalty: reduces score when non-zero (contribution to score: -0.0667)
Under-cited
Present in run, outside top 50
Low-cite candidate pool (see docs/candidate-pool-low-cite.md v0): core corpus, recency floor, citation ceiling, title+abstract gate; popularity penalty among pool members only. Semantic and bridge not yet modeled.
Signals: citation_velocity=0.0000, topic_growth=0.4167, diversity_penalty=0.0000
Semantic match: not computed for this run
Recent attention: low; used in final ranking (contribution to score: 0.0000)
Topic momentum: medium; used in final ranking (contribution to score: 0.2917)
Cross-cluster signal: not computed for this run
Pool popularity penalty: reduces score when non-zero (contribution to score: 0.0000)
Recent spatial audio techniques involve separating multichannel signals into direct and background parts. However, determining parameters for localizing short sound sources in background sounds remains challenging due to the limited knowledge of spatial hearing resolution. This paper investigates the localization performance when short bursts in the median plane are presented with spectrally similar, horizontally spread broadband noise. Listening tests examined target stimuli in different median plane locations with and without masker noises, using elevation gain, bias, and error rate to evaluate localization performance. The target stimuli comprised aperiodically repeated multiple-burst stimuli with different burst rates and levels and single-burst stimuli with varied duration and levels. The results showed that the burst rate of multiple-burst stimuli had a weak systematic effect on all the criteria for localization performance, regardless of noise. However, extending the duration of single-burst stimuli increased the elevation gain, and the added noise further improved the localization performance. The masker also improved localization performance when the sound level increased, while unmasked stimuli had the opposite effect. The optimal conditions for improving localization performance with background noise found in this study were a signal-to-noise ratio of ≥18 dB.
Neighborhood labels
Topic labels are imported metadata and can be noisy; use them as coarse navigation hints, not authoritative classifications.
Image and Signal Denoising MethodsStructural Health Monitoring Techniques
Neighbor surface
Similar papers use a separately configured neighbor embedding; it may differ from the embedding version used by the current ranked run.
No embedding-backed neighbors available for this paper/version yet.
Next handoff
01
Use Recommended to see whether this paper behaves like an emerging or undercited signal in the current ranked feed, or how it appears on the bridge preview / diagnostics view.
02
Use Trends to understand whether its attached labels are heating up or cooling down inside the curated corpus.
03
Use Evaluation to compare the dossier readout against citation and recency baselines for the same resolved family run.