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Record W4387741496 · doi:10.1002/lol2.10358

Acoustic twilight: A year‐long seafloor monitoring unveils phenological patterns in the abyssal soundscape

2023· article· en· W4387741496 on OpenAlexfundno aff
Tzu‐Hao Lin, Shinsuke Kawagucci

Bibliographic record

VenueLimnology and Oceanography Letters · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersSwine Innovation Porc
KeywordsSoundscapeDiel vertical migrationAbyssal zoneOceanographyForagingAbyssal plainMesocosmTwilightEcologyBiologyGeologyEcosystemSound (geography)Paleontology

Abstract

fetched live from OpenAlex

Abstract Despite the perpetual darkness of the deep sea, contrasting the sunlit epipelagic waters, many deep‐sea organisms exhibit rhythmic activities. To discern environmental cues that may serve as entrainment signals for deep‐sea organisms, this study investigated the soundscape of the abyssal plain south of Minamitorishima Island. Our analysis revealed clear diel and seasonal patterns, primarily driven by evening fish choruses and marine mammal vocalizations. These evening choruses, discernible above the background noise, likely serve as a circadian time cue for organisms capable of perceiving them within the aphotic depths. In addition, the frequent detection of whistles and echolocation clicks suggests this region functions as a foraging ground for marine mammals. These acoustic cues might guide organisms with auditory capabilities toward habitats rich in sinking food debris and whale falls. By elucidating the ecological processes shaping abyssal soundscape dynamics, these findings open new directions for further exploration in deep‐sea chronobiology.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations10
Published2023
Admission routes1
Has abstractyes

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