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Record W2557236788 · doi:10.4043/27369-ms

A Revised Basis for Iceberg Areal Density Values for Risk Analysis

2016· article· en· W2557236788 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 institutionsCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsIcebergSubmarine pipelineGeolocationAerial surveyMerge (version control)MeteorologySea iceGeographyGeologyRemote sensingOceanographyComputer science

Abstract

fetched live from OpenAlex

Abstract Iceberg areal density is one of the most important and challenging parameters to define accurately for offshore petroleum exploration. The two data sources for iceberg areal density considered here are aerial reconnaissance data collected by the International Ice Patrol (IIP) and iceberg charts which merge aerial reconnaissance data with other observations and model output. The IIP operates regular flights to monitor iceberg hazards to transatlantic transportation off the Canadian East Coast. The IIP and Canadian Ice Service (CIS) work together to generate daily ice charts year-round to provide the most reliable and timely information about the iceberg distribution by defining an iceberg limit to minimize risk of iceberg collision to transportation. The purpose of the iceberg charts is to promote safe maritime operations and to inform mariners about the latest ice conditions in navigable Canadian waterways and transatlantic shipping lanes in international waters. With navigational safety as its primary goal, the IIP develops the iceberg limit and distribution for vessels planning to avoid encountering icebergs completely. These warnings therefore are generally more conservative than on-site observations. The daily ice chart is created based on the data provided by various sources and is modified regularly by adding new sightings and applying drift and deterioration models to previous sightings. Among all the sources, aerial reconnaissance provides the most up-to-date information on iceberg conditions, and are generally conducted between February and July. For a better understanding of the influence of the data sources, iceberg frequency values using aerial reconnaissance data and charts were compared for a common period of time for several locations. Comparing the results, it was observed that results from aerial reconnaissance data analysis are typically lower than results from chart data i.e., more icebergs were reported in the ice charts than were sighted by aerial reconnaissance. This is consistent with IlP's conservative approach in reporting iceberg hazards to transatlantic mariners. Using the most appropriate source of data to identify the risk that icebergs pose for offshore petroleum production facilities is essential. The objective of this paper is to assess the discrepancies between data provided through aerial reconnaissance and that included in the daily iceberg charts.

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)0.001
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 score0.388
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.227
Teacher spread0.213 · 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