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Record W3165785854

Assessing Hydrocarbon presence in the waters of Port au Port bay, Newfoundland and Labrador, for AUV oil spill delineation tests

2020· article· en· W3165785854 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUTAS Research Repository · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsBayPort (circuit theory)Environmental scienceWater columnHydrology (agriculture)Sampling (signal processing)Petroleum seepGeologyOceanographyEngineeringGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

The waters adjacent to the Port au Port Peninsula, in Port au Port Bay, Newfoundland andLabrador, are known to be subject to release of hydrocarbons from natural oil seeps and oldabandoned oil wells. An investigation was done to determine whether there were sufficient oilcompounds present for planned autonomous underwater vehicle (AUV) test missions to developadaptive sampling algorithms to delineate oil spills. Fluorometers were used in-situ to measureoil concentrations. Oil-and-water samples were taken at selected waypoints for chemical analysisin the laboratory to validate the sensor measurements and to provide a ground truth. Only oneof the fluorometers was found to have a minimum detection level that was capable of sensingthe hydrocarbons in the water column. The water sample results indicated hydrocarbon levelsup to almost 30 ppm in the east side of the bay, just to the west of Shoal Point, but no detectablelevels on the west side of the bay. It was concluded that it would be possible to operate an AUVon a planned fixed mission with a pre-programmed search path and record the levels of signaldetected from fluorometers or other sensors. However, it would be difficult to implement anadaptive mission in this case because of the low levels of sensor signals resulting from the lowconcentrations of hydrocarbon present.

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)0.001
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 score0.385
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.333
Teacher spread0.282 · 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