MétaCan
Menu
Back to cohort

Environmental Assessment of Railway Wheels for Long-Term Moorings in the Juan de Fuca Ridge

2024· article· en· W4404689054 on OpenAlexaff
Robert A. Duff, Kathryn Moran, Kohen W. Bauer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicEnvironmental and Ecological Studies
Canadian institutionsOcean Networks Canada Society
Fundersnot available
KeywordsRidgeTerm (time)GeologyEnvironmental scienceMarine engineeringAeronauticsGeodesyEngineeringPhysicsPaleontology

Abstract

fetched live from OpenAlex

Railway wheels have long been used as convenient and low-cost anchors, but while there are a number of advantages to their use, their impact on local marine environments has not yet been extensively examined. This study explores their potential impact on marine ecosystems, including substrate disturbance, habitat alteration, and effects on marine biodiversity. As well, the study analyzes available research on deep-sea corrosion mechanisms to investigate the leaching of metals from railway wheels as a result of marine corrosion in consideration of environmental regulations regarding marine protected areas (MPA) like the Tang. <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\underline{\mathrm{G}}\text{wan}-\text{ha}\check{\mathrm{c}}\mathrm{x}^{\mathrm{w}}\text{iqak}$</tex>-Tsigis MPA. By analysing existing research and presenting a comprehensive overview, as well as reviewing surveillance of current railway wheel anchors, this article aims to assess the feasibility of such anchoring methods in terms of long-term environmental sustainability and contribute to a better understanding of the environmental tradeoffs associated with the use of railway wheels as deep-sea anchors.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.277
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicEnvironmental and Ecological StudiesFrench-language works237,207