MétaCan
Menu
← Back to cohort
Record W6929147869 · doi:10.48336/4z0s-af38

Effects of wind, waves, and currents on icebergs and surface floats in the Labrador Sea: a modeling study

2023· article· en· W6929147869 on OpenAlexaffabout

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2023
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsIcebergSubmarine pipelineSea-surface heightSea surface temperatureStormOcean surface topographyBuoySea ice

Abstract

fetched live from OpenAlex

Icebergs are major indicators of climate change. In Newfoundland, icebergs attract tourists while simultaneously posing a threat to ships and offshore oil platforms. Research is carried out on a model study of the dynamics of icebergs and surface floats in the Labrador Sea. In this study, the iceberg model is forced with data of wind above the ocean surface, surface waves and ocean currents. The wind and surface wave characteristics are acquired from the hourly ECMWF reanalysis (ERA5), while the ocean current, sea-surface height and sea surface temperature data are from MERCATOR Ocean International daily reanalysis for the year 2008. In the Labrador Sea, for smaller icebergs the primary balance is between the air and water drag, while for larger icebergs it is between three forces: the air and water drag and the combined Coriolis and pressure force. Floats are primarily driven by the Ekman component of surface velocity. Storms passing over the Labrador Sea cause significant variability in the movements of icebergs and floats.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.876

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.290
Teacher spread0.260 · 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 designSimulation or modeling
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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueMemorial University Research Repository (Memorial University)→Same topicGlobal Maternal and Child Health→French-language works237,207→