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Record W4213276584 · doi:10.1126/sciadv.abl7605

Sunlight-driven dissolution is a major fate of oil at sea

2022· article· en· W4213276584 on OpenAlexfundno aff
Danielle Haas Freeman, Collin P. Ward

Bibliographic record

VenueScience Advances · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsnot available
FundersFisheries and Oceans CanadaCereal Partners WorldwideNational Science Foundation
KeywordsDissolutionEnvironmental scienceDeepwater horizonWavelengthSunlightOil spillEnvironmental chemistryChemistryMaterials scienceOpticsEnvironmental engineeringPhysicsOptoelectronics

Abstract

fetched live from OpenAlex

Oxygenation reactions initiated by sunlight can transform insoluble components of crude oil at sea into water-soluble products, a process called photo-dissolution. First reported a half century ago, photo-dissolution has never been included in spill models because key parameters required for rate modeling were unknown, including the wavelength and photon dose dependence. Here, we experimentally quantified photo-dissolution as a function of wavelength and photon dose, making possible a sensitivity analysis of environmental variables in hypothetical spill scenarios and a mass balance assessment for the 2010 Deepwater Horizon (DwH) spill. The sensitivity analysis revealed that rates were most sensitive to oil slick thickness, season/latitude, and wavelength and less sensitive to photon dose. We estimate that 3 to 17% (best estimate 8%) of DwH surface oil was subject to photo-dissolution, comparable in magnitude to other widely recognized fate processes. Our findings invite a critical reevaluation of surface oil budgets for both DwH and future spills at sea.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.239
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations33
Published2022
Admission routes1
Has abstractyes

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