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Record W2079063215 · doi:10.7901/2169-3358-2005-1-1001

LASER FLUOROSENSOR DEMONSTRATION FLIGHTS AROUND THE SOUTHERN COAST OF NEWFOUNDLAND

2005· article· en· W2079063215 on OpenAlexaffabout
Carl E. Brown, Mervin F. Fingas, Richard Marois

Bibliographic record

VenueInternational Oil Spill Conference Proceedings · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsPetroleum seepRemote sensingEnvironmental scienceAerial surveyOceanographyMeteorologyGeographyGeologyEcology

Abstract

fetched live from OpenAlex

ABSTRACT Several oil spill remote sensing flights were conducted by Environment Canada off the Southern coast of Newfoundland, Canada in late February, early March 2004. These flights were undertaken to demonstrate the capabilities of the Scanning Laser Environmental Airborne Fluorosensor (SLEAF) in real-life situations in the North Atlantic and Newfoundland coastal regions in late winter weather conditions. Geo-referenced infrared, ultraviolet, color video and digital still imagery was collected along with the laser fluorosensor data. Brief testing of a Generation III night vision camera was also conducted. Flights were conducted in the shipping lanes around the Newfoundland coast, out to the Hibernia and Terra Nova oil platforms and over known oil seep areas. Details of the analysis of laser fluorescence data collected during these flights will be presented along with a summary of the remote sensing flights.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.467
Threshold uncertainty score0.939

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.013
GPT teacher head0.228
Teacher spread0.214 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations8
Published2005
Admission routes2
Has abstractyes

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