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A New Field Guide For Freshwater Shoreline Response

2021· article· en· W4205380821 on OpenAlexaffabout
Sonia Laforest, E H Owens, Leanne Zrum, Patrick Lambert, Shannon M. MacDonald, Stéphane Grenon

Bibliographic record

VenueInternational Oil Spill Conference Proceedings · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsCollege of the RockiesEnvironment and Climate Change Canada
Fundersnot available
KeywordsShoreOil spillThreatened speciesField (mathematics)Environmental scienceEnvironmental resource managementEnvironmental planningGeographyOceanographyEnvironmental protectionGeologyEcologyHabitat

Abstract

fetched live from OpenAlex

ABSTRACT Environment and Climate Change Canada (ECCC) has developed a series of field guides to provide technical support tools for decisions regarding the evaluation of freshwater and marine shorelines and treatment options during an oil spill response. The new Freshwater Shoreline Response Guide is aligned with and complements the most recent editions of the ECCC Shoreline Cleanup Assessment Technique (SCAT) Manual (ECCC, 2018) and the ECCC Field Guide to Oil Spill Response on Marine Shorelines (ECCC, 2016). ECCC is engaged to provide science-based information to the spill response community and develop an expertise in spill response. The purpose of the Freshwater Shoreline Response Field Guide is to provide advice and guidance on the protection and treatment of freshwater shorelines threatened or affected by an oil spill. This Field Guide focuses on conventional tactics normally available to responders and appropriate for freshwater shoreline environments. The content of the Field Guide is organized to describe key elements of: Health and safety for field teamsNet Environmental Benefit Analysis (NEBA) / Spill Impact Mitigation Assessment (SIMA)Freshwater environmentsOil fate and behaviour in freshwater environmentsResponse – planning, treatment, special topics, and completion and monitoring

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0130.000

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 head0.016
GPT teacher head0.268
Teacher spread0.252 · 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 designNot applicable
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

Citations0
Published2021
Admission routes2
Has abstractyes

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