Multibeam bathymetry and selected perspective views offshore San Diego, California
Bibliographic record
Abstract
This set of two posters consists of a map on one sheet and a set of seven perspective views on the other. The ocean floor image was generated from multibeam-bathymetry data acquired by Federal and local agencies as well as academic institutions including: - U.S. Geological Survey mapped from the La Jolla Canyon south to the US-Mexico border using a Kongsberg Simrad multibeam echosounder system (MBES) (March - April 1998). Data and metadata available at http://pubs.usgs.gov/of/2004/1221/. - Woods Hole Oceanographic Institution and SCRIPPS Institution of Oceanography mapped the majority of the La Jolla Fan Valley including the sea floor to the north and south of the valley using a Seabeam 2100 MBES. Data available at http://www.ngdc.noaa.gov/mgg/bathymetry/multibeam.html. Survey ID, AT07L09, Chief Scientists, Barrie Walden and Joseph Coburn (April 2002). - California State University, Monterey Bay, mapped Scripps Canyon and the head of La Jolla Canyon using a Reson 8101 MBES (October 2001). Data and metadata available at http://seafloor.csumb.edu/SFMLwebDATA.htm. This work was funded by the California Department of Fish and Game California Coastal Conservancy, San Diego Association of Governments (SANDAG), California Department of Fish and Game, and Fugro Pelagos mapped the nearshore region out to about 35-40 m. - The sea floor within this image that has not been mapped with MBES is filled in with interpreted bathymetry gridded from single-beam data available at http://www.ngdc.noaa.gov/mgg/bathymetry/hydro.html. Depths are in meters below sea level, which is referenced to Mean Lower Low Water.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".