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Record W2049286703 · doi:10.7901/2169-3358-2001-2-923

RESPONDING TO THE BIG SPILL OF 20111

2001· article· en· W2049286703 on OpenAlex
Bill Lehr, Ron Goodman

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.

Bibliographic record

VenueInternational Oil Spill Conference Proceedings · 2001
Typearticle
Languageen
FieldComputer Science
TopicDigital and Cyber Forensics
Canadian institutionsImperial Oil (Canada)
Fundersnot available
KeywordsDisseminationOil spillThe InternetComputer scienceEnvironmental scienceEnvironmental resource managementTelecommunicationsWorld Wide WebEnvironmental engineering

Abstract

fetched live from OpenAlex

ABSTRACT The authors use a hypothetical spill incident 10 years in the future to examine the possible advances of spill response technology. The status of remote sensing at present, as well as its capabilities a decade hence, are discussed. The authors examine spill communication improvements, speculate on the use of the Internet to disseminate spill information, and examine electronic database systems for slick management. Progress in effectively using alternative cleanup strategies such as in situ burning and dispersants are reviewed, along with some of the likely impediments to their use in spills of 2011. Spill trajectory and behavior forecasting techniques of tomorrow are discussed in light of the expected continuing advance in computer technology. The authors review the likelihood that these new capabilities would actually be implemented. The resulting picture is a mixed one. Possible positive and negative scenarios are described.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.415

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.030
GPT teacher head0.254
Teacher spread0.224 · 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