Inversion for geometric and geoacoustic parameters of Haro Strait data using <i>a</i> <i>posteriori</i> density functions
Bibliographic record
Abstract
Inversions for geometric and geoacoustic parameters of a multitone, multishot experiment are examined using a posteriori probability distributions based on simulated annealing importance sampling. Data were collected as part of the matched-field tomography component of the Haro Strait PRIMER Experiment of June/July 1996 which can be categorized as low frequency, shallow water, and bathymetrically complex. The inherently unquantifiable sources of mismatch between data and model in environmentally complex systems favor a statistical approach over more conventional global optimization techniques. Large uniqueness and parameterization error complicate an accurate interpretation of the data covariance matrix necessary for appropriate choice of Gibbs sampling temperature. Trends in density functions are therefore examined as the relative sampling temperature is lowered. The mean and half-width value of the density distribution for each parameter are evaluated as a function of sampling temperature. [Work supported by ONR.]
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".