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Integration of the Motus Wildlife Tracking System to the NOAA GOES Data Collection System for Offshore Wildlife Telemetry Applications

2024· article· en· W4404688549 on OpenAlexaffabout
Daniel Gillies, Pamela H. Loring, Nathan Holcomb, David Ilogho, William Dronen, Zhiqun Deng, Brett Betsill, Beau Backus, Stuart A. Mackenzie, Thorsten von Eicken

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsBirds Canada
Fundersnot available
KeywordsWildlifeTelemetrySubmarine pipelineRemote sensingComputer scienceTracking (education)Data collectionTracking systemWildlife conservationFisheryGeographyOceanographyTelecommunicationsGeologyEcologyArtificial intelligence

Abstract

fetched live from OpenAlex

The development of offshore wind energy facilities has created a renewed demand for monitoring of migratory species which may be influenced by the presence of these installations along their migration routes. The United States Fish and Wildlife Service (USFWS), in coordination with Birds Canada and other proj ect collaborators has proposed the use of the Motus Wildlife Tracking System for monitoring migratory bird and bat presence and movement in proximity to offshore wind energy facilities. Motus is a radio frequency (RF) based tag/receiver system that detects RF tagged individuals traveling in proximity to a Motus receiver station, logs their unique identification, and relays it back to a centralized Motus database maintained by Birds Canada. The location of offshore wind energy facilities far from traditional terrestrial networks drives a demand for satellite connectivity for the receiver stations. The National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellites (GOES) host an environmental radio relay system, the GOES Data Collection System (DCS) which connects remote in-situ environmental monitoring platforms, also known as Data Collection Platforms (DCPs) with researchers throughout the western hemisphere. This relay service is free to use for U.S. federal, state, and local government agencies, in addition to international government agencies and research organizations with a U.S. government sponsor. By integrating Motus receivers with GOES DCS transmitters, near real-time migratory species telemetry data can be relayed from remote locations, such as offshore wind energy facilities, and delivered to the Motus database. This integration enables a larger distribution of Motus receiver stations both offshore and terrestrially by providing a reliable, service fee free link that can deployed anywhere within the footprint of the GOES spacecraft and follow-on NOAA geostationary satellite constellations. NOAA is also performing testing to validate the use of the latest GOES DCS transmitters and communications protocols in dynamic offshore settings, for use on buoys and ocean floats, with Motus receivers as a payload or other environmental in-situ sensors. While GOES DCS was used on buoys in the past, notably by the NOAA National Data Buoy Center, power requirements and performance limited its adoption. NOAA is revalidating DCS use on buoys and floats by benchmarking existing transmitter performance in dynamic sea surface conditions and evaluating performance of enhanced forward error correction and modulation schemes that will enable DCS operation in signal to noise ratio challenged environments.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.005

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.

Opus teacher head0.038
GPT teacher head0.278
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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