Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".