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Record W2559561788 · doi:10.4043/27445-ms

Operational Ocean Ice Prediction System Validation for the Canadian Arctic and Northwest Atlantic

2016· article· en· W2559561788 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArctic Technology Conference · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsEnvironment and Climate Change CanadaFisheries and Oceans Canada
FundersJapan Aerospace Exploration AgencyU.S. NavyNational Oceanic and Atmospheric Administration
KeywordsSea iceEnvironmental scienceArcticOcean observationsClimatologyMeteorologySearch and rescueOceanographyComputer scienceGeologyGeography

Abstract

fetched live from OpenAlex

Abstract Ocean-Ice prediction systems maximize the information value of scarce in-situ ocean and ice observations. They provide assessed and forecast ocean and ice conditions that combine satellite observations and in-situ observations along with ocean and ice physics. Such information supports many applications and marine operations including navigation in open and ice covered waters, search and rescue drift prediction and oil spill drift prediction (with and without ice cover). Additional benefits include more accurate weather predictions through coupling of prediction systems and better oceanographic information support for marine resources and marine life applications. With decreasing ice coverage and increased navigation activity in the Arctic, the availability of operational ocean and ice predictions are important for ensuring safety of marine operations as well as timely responses to marine emergencies. We review the validation methodology of ocean ice prediction systems for the Canadian North under the Canadian Operational Network of Environmental PredicTion System (CONCEPTS) activities. CONCEPTS is an MOU governing an ocean, ice and atmospheric prediction collaboration of three government departments: National Defense, Environment and Climate Change Canada and Fisheries and Oceans Canada. Validation metrics include comparisons of ice and ocean forecast parameters against satellite (AMSRE Radiometry, Cryosat Altimetry) and in-situ observations from ships, moorings and autonomous floats. Forecast performance for the years 2015 and 2016 are presented herein. The overall goal is to estimate forecast reliability through development of vetted procedures for providing performance statistics against observations, both in real time and delayed mode for the Canadian CONCEPTS Ocean Ice Prediction systems. The approach is part of the GODAE Ocean View international collaboration network in Operational Oceanography for comparing ocean ice predictions against observations. Ultimately we aim to provide a framework by which participating ocean operators can provide in-situ observations from their assets (ships, rigs, ice camps, etc.) and receive performance stats (year in review, month in review) of ocean and ice prediction systems against the observations they provide.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.838

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 studies0.0010.000
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 head0.011
GPT teacher head0.188
Teacher spread0.177 · 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