MétaCan
Menu
Back to cohort
Record W4403826572 · doi:10.1109/iotm.001.2400002

Connected Internet of Things for Monitoring and Tracking of Endangered Whales

2024· article· en· W4403826572 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Internet of Things Magazine · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of OttawaConcordia University
Fundersnot available
KeywordsEndangered speciesWhaleTracking (education)FisheryInternet of ThingsThe InternetGeographyEnvironmental scienceInternet privacyComputer scienceWorld Wide WebBiologyEcologySociologyHabitat

Abstract

fetched live from OpenAlex

Connected Internet of Things (CIoT) integrates Internet of Things (IoT) in different domains (e.g., spatial, aerial, terrestrial, and underwater). CIoT enables monitoring and tracking in remote and large geographic areas, such as the Earth's poles, forests, and oceans. In this article, we envision a CIoT system for the near-real-time monitoring of endangered whale species. In the envisioned system, very high-resolution images from satellites and Internet of CubeSats shall be used for the autonomous detection and location determination of endangered whales. The obtained locations shall be used to determine the trajectory of surface autonomous vessels that will temporarily deploy an Internet of aerial and underwater things for the near-real-time monitoring of detected whales. We discuss the main entities involved in the envisioned architecture, data flows, and communication paradigms needed to implement the proposed CIoT architecture and the challenges to empower the envisioned system. We also point out future research directions to be solved towards a CIoT system for whale monitoring.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.266
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