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Record W4214714881 · doi:10.3390/geosciences12030110

OpenMetBuoy-v2021: An Easy-to-Build, Affordable, Customizable, Open-Source Instrument for Oceanographic Measurements of Drift and Waves in Sea Ice and the Open Ocean

2022· article· en· W4214714881 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

VenueGeosciences · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCarleton UniversityEnvironment and Climate Change Canada
Fundersnot available
KeywordsFirmwareComputer scienceScientific instrumentConsumablesInstrumentation (computer programming)Systems engineeringSoftwareOpen source hardwareReal-time computingRemote sensingOpen sourceComputer hardwareEngineeringOperating system

Abstract

fetched live from OpenAlex

There is a wide consensus within the polar science, meteorology, and oceanography communities that more in situ observations of the ocean, atmosphere, and sea ice are required to further improve operational forecasting model skills. Traditionally, the volume of such measurements has been limited by the high cost of commercially available instruments. An increasingly attractive solution to this cost issue is to use instruments produced in-house from open-source hardware, firmware, and postprocessing building blocks. In the present work, we release the next iteration of our open-source drifter and wave-monitoring instrument, which follows these solution aspects. The new design is significantly less expensive (typically by a factor of 5 compared with our previous, already cost-effective instrument), much easier to build and assemble for people without specific microelectronics and programming competence, more easily extendable and customizable, and two orders of magnitude more power-efficient (to the point where solar panels are no longer needed even for long-term deployments). Improving performance and reducing noise levels and costs compared with our previous generation of instruments is possible in large part thanks to progress from the electronics component industry. As a result, we believe that this will allow scientists in geosciences to increase by an order of magnitude the amount of in situ data they can collect under a constant instrumentation budget. In the following, we offer (1) a detailed overview of our hardware and software solution, (2) in situ validation and benchmarking of our instrument, (3) a fully open-source release of both hardware and software blueprints. We hope that this work, and the associated open-source release, will be a milestone that will allow our scientific fields to transition towards open-source, community-driven instrumentation. We believe that this could have a considerable impact on many fields by making in situ instrumentation at least an order of magnitude less expensive and more customizable than it has been for the last 50 years, marking the start of a new paradigm in oceanography and polar science, where instrumentation is an inexpensive commodity and in situ data are easier and less expensive to collect.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.028
GPT teacher head0.245
Teacher spread0.218 · 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