Application of the City Ditty soundscape tool in an interdisciplinary urban park design competition
Bibliographic record
Abstract
The user-centered soundscape design tool City Ditty has been supplemented with local data from Santiago, Chile, to be used in the design of an urban park in which the perception of natural soundscapes dominates over other sound sources. This local data comprises a 3D model of the space, ambisonic recordings of urban background noise, 3D assets and recordings of sound sources (e.g. regional birds). This sketchpad tool is being adapted to local particularities to increase its performance in biophilic design interventions in the target area, and to be able to auralize the proposed 3D park models. These interventions arise from a design competition in interdisciplinary teams and their results are evaluated through individual auralization tests. The design proposal whose soundscape gets the highest subjective rating will be optimized by iterating listening tests and adjusting the design parameters. Once optimized, the final design model can be experienced at City Ditty through head-mounted VR binaural playback as well as an immersive multi-channel playback system.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".