Spatial field shifts in ocean acoustic environmental sensitivity analysis
Bibliographic record
Abstract
This article examines the effects of spatial field shifts in ocean acoustic environmental sensitivity analysis. Acoustic sensitivity studies are typically based on comparing acoustic fields computed for a reference environmental model and for a perturbed model in which one or more parameters have been changed. The perturbation to the acoustic field due to the perturbed environment generally includes a component representing a spatial shift of the field (i.e., local field structure remains coherent, but shifts in range and/or depth) and a component representing a change to the shifted field. Standard sensitivity measures based on acoustic perturbations at a fixed point can indicate high sensitivity in cases where the field structure changes very little, but is simply shifted by a small spatial offset; this can conflict with an intuitive understanding of sensitivity. This article defines and compares fixed-point and field-shift corrected sensitivity measures. The approaches are illustrated with examples of deterministic sensitivity (i.e., sensitivity to a specific environmental change) and stochastic sensitivity (sensitivity to environmental uncertainty) in range-independent and range-dependent environments.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".