Rapid Communication / Communication RapideAcoustic seabed classification: improved statistical method
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Huge amounts of money will be spent by industrialized nations during the next decades to obtain detailed maps of continental shelf seabeds. These maps, which will allow a more rational exploitation of the sea floor, are needed to assess the impact of anthropic activities. The statistical method of analysis of echosounder backscatter data described in this paper presents several improvements over existing techniques. The steps are as follows. (i) The backscatter data are decomposed mathematically into a number of quantitative variables, which are subjected to principal component analysis (PCA). (ii) Principal components representing 9599% of the variation are used in a K-means partitioning procedure. A statistical criterion indicates what the number of groups is that best reflects the variability of the data. (iii) The groups are then plotted on maps of the survey area. Insofar as the mathematical decomposition produces variables that reflect the variations of the physical nature and composition of the seabed, the classes of the partition will correspond to different seabed types. Free software (The Q Package) implementing this method is available at http://www.fas.umontreal.ca/biol/legendre/.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it