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Record W2953200633 · doi:10.3133/cir13063f

Hurricane Katrina flooding and oil slicks mapped with satellite imagery

2007· article· en· W2953200633 on OpenAlexfundno aff
Russell Rykhus, Zhong Lu

Bibliographic record

VenueU.S. Geological Survey circular/U.S. Geological Survey Circular · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsnot available
FundersCanadian Space AgencyFederal Emergency Management AgencyU.S. Geological SurveyCentre National d’Etudes Spatiales
KeywordsRacing slickThematic MapperFlooding (psychology)DebrisSatellite imageryFlood mythThematic mapOil spillRemote sensingSubmarine pipelineEnvironmental scienceCartographyMeteorologyGeographyGeologyOceanographySynthetic aperture radarArchaeologyEnvironmental protection

Abstract

fetched live from OpenAlex

A multiple-database approach that combined remotely sensed data from Radarsat-1 and Landsat Thematic Mapper Plus (ETM+) imagery was used to map Hurricane Katrinainduced flooding and to identify offshore oil slicks. Maps depicting the areal extent of flooding, oil slicks, and floating debris provide vital information to emergency managers for directing floodrelief efforts and the clean-up of polluted waters.

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 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)0.013
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.229
Teacher spread0.207 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations9
Published2007
Admission routes1
Has abstractyes

Explore more

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