MANGA - (Tag) Habitat use of oceanic manta rays
Bibliographic record
Abstract
This is the OBIS extraction of the FACT Network and Bureau of Ocean Energy Management (BOEM) MANGA - (Tag) Habitat use of oceanic manta rays, consisting of the release tagging metadata, i.e. the location and date when the tagged animal was released, and summarized detection events of tagged individuals. If readers are interested in the source dataset they may also inquire with the project PIs as listed here or on the OTN web site (https://members.oceantrack.org/project?ccode=FACT.MANGA). Abstract:The purpose of this study is to understand how movements and site fidelity of endangered oceanic manta rays (Mobula birostris) affect the risk of this species interacting with the Bureau of Ocean Energy Management (BOEM) marine mineral extraction or associated mitigation activities as part of their Marine Minerals Program (MMP). Acoustic telemetry will be used to determine habitat use patterns within existing receiver arrays at the Canaveral Shoals sand borrow area, whereas animal-borne inertial tags will be used to characterize behavior at fine spatial and temporal scales. Together, these techniques leverage the target species as a mobile oceanographic platform advancing the utility of animal telemetry for ocean monitoring while providing data on the risks of negative interactions between endangered megafauna and mineral extraction activities, thus facilitating improved mitigation. Data produced from this study will feed into robust education and outreach programs underway at Georgia Aquarium, which is one of the world’s largest public aquariums and features giant manta rays as a flagship exhibit species.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".