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Record W1797997818

A review of noise impacts from offshore oil-gas production activities on the marine biota

2007· review· en· W1797997818 on OpenAlexaffvenue
Sharmin Sultana, Zhi Chen

Bibliographic record

VenueCanadian acoustics · 2007
Typereview
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsConcordia University
Fundersnot available
KeywordsMarine mammalEnvironmental scienceBiotaNoise pollutionNoise (video)FisheryMarine pollutionOceanographyPollutionEcologyBiologyComputer scienceGeologyNoise reduction
DOInot available

Abstract

fetched live from OpenAlex

A review on marine noise that originates from vessel traffic, oil-gas exploration activities, machinery and propeller noise, research activities, military sonar, and dredging are discussed. Some of the impacts from marine noise pollution include, egg-larvae mortality, feeding and breeding problem, stress, damage of tissue and organs, masking, hearing loss, behavioral changes, and communication problem. Noise pollution affects marine mammals and fish to experience pathological effects, behavioral changes, and feeding-mating- breeding-nursing disruptions. Long term monitoring is vital for critical and sensitive species in areas of concern such as restricted migratory routes, spawning area, feeding-breeding-nursing grounds, and resting places. A multidisciplinary study was undertaken by the US Navy to develop a software by integrating expertise from acoustics, oceanographic modeling, marine mammal biology, oceanography, naval operations, and environmental compliance for simulating animal movement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.008
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.045
GPT teacher head0.281
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2007
Admission routes2
Has abstractyes

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