Utilizing New Multibeam Sonar Datasets to Map Potential Locations of Sensitive Benthic Habitats in the U.S. Atlantic Extended Continental Shelf
Bibliographic record
Abstract
Recently completed multibeam sonar datasets of the U.S. Atlantic Extended Continental Shelf (ECS) area provide bathymetry and acoustic backscatter data that can be utilized in combination with other oceanographic data to help identify Habitats of Particular Concern (HAPCs), such as deepwater corals. Multibeam sonar data was collected by the University of New Hampshire’s Center for Coastal and Ocean Mapping/Joint Hydrographic Center (CCOM/JHC) on four different cruises between 2004-2012, and by multiple cruises of the NOAA ship Okeanos Explorer between 2011-2013. These two new multibeam sonar datasets provide a historic new level of detail to our understanding of the Northwest Atlantic seafloor from Florida to the Canadian maritime boundary and from the edge of the continental shelf to the deep ocean. CCOM/JHC has embarked on a research effort to evaluate ways in which to use the new multibeam data sets from the Atlantic Margin, along with other existing ancillary datasets, to generate marine ecological classification maps and potential habitat prediction maps useful for supporting Ecosystem-Based Management. The initial component of this work involves processing the data using QPS Fledermaus and ESRI ArcGIS software to derive sediment classification predictions and terrain descriptors. Substrate characterization and thematic classifications derived using the “GEOCODER” code from CCOM/JHC are used in combination with seafloor groundtruth data and oceanographic model output to identify potential habitat areas. Bathymetry and backscatter datasets collected with different sonar systems of varying resolution are compared to examine differences in interpreted properties of seafloor substrates within areas of overlapping hydrographic surveys. Results of this work are intended to substantially improve predictive models of potential coldwater coral distribution in the Atlantic ECS area. Future phases of this research effort will apply NOAA’s Coastal and Marine Ecological Classification Standard (CMECS) to the U.S. Atlantic ECS area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".