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Record W2744642560

Sound Source Segregation in the Acoustic Parasitiod Fly Ormia ochracea

2012· dissertation· en· W2744642560 on OpenAlexfundno aff
Norman Lee

Bibliographic record

VenueTSpace · 2012
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSound (geography)AcousticsPhysics
DOInot available

Abstract

fetched live from OpenAlex

Sound source localization depends on the auditory system to identify, recognize, and segregate elements of salient sources over distracting noise. My research investigates sensory mechanisms involved in these auditory processing tasks of an insect hearing specialist, to isolate individual sound sources of interest over noise. I first developed quantitative methods to determine signal features that the acoustic parasitoid fly Ormia ochracea (Diptera: Tachinidae) evaluate for host cricket song recognition. With flies subjected to a no-choice paradigm and forced to track a switch in the broadcast location of test songs, I describe several response features (distance, steering velocity, and angular orientation) that vary with song pulse rate preferences. I incorporate these response measures in a phonotaxis performance index that is sensitive to capturing response variation that may underlie song recognition. I demonstrate that Floridian O. ochracea exhibit phonotaxis to a combination of pulse durations and interpulse intervals that combine to a range of accepted pulse periods. Under complex acoustic conditions of multiple coherent cricket songs that overlap in time and space, O. ochracea may experience a phantom source illusion and localize a direction between actual source locations. By varying the temporal overlap between competing sources, I demonstrate that O. ochracea are able to resolve this illusion via the precedence effect: exploitation of small time differences between competing sources to selectively localize the leading over lagging sources. An increase in spatial separation between cricket song and masking noise does not reduce song detection thresholds nor improve song localization accuracy. Instead, walking responses are diverted away from both song and noise. My findings support the idea that the ears of O. ochracea function as bilateral symmetry detectors to balance sound intensity, sound arrive time differences, and temporal pattern input to both sides of the auditory system. Asymmetric acoustic input result in corrective turning behaviour to re-establish balance for successful source localization.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.981

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)0.0000.000

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 head0.047
GPT teacher head0.290
Teacher spread0.243 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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