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Record W7071192124

SERPENT Cruise Reports July 2002 to December 2006

2007· other· en· W7071192124 on OpenAlexaboutno aff

Bibliographic record

VenueNERC Open Research Archive (Natural Environment Research Council) · 2007
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCruiseGeneral partnershipSerpent (symbolism)Remotely operated underwater vehicleNautilusMarine researchIndian ocean
DOInot available

Abstract

fetched live from OpenAlex

The SERPENT Project, Scientific & Environmental ROV Partnership using Existing iNdustrial Technology, is a collaboration between world leading scientific institutions and companies associated with the oil and gas industry. SERPENT is hosted at the National Oceanography Centre, Southampton (NOCS), one of the worlds’ largest research and teaching organisations specialising in deep-sea science and oceanography. SERPENT encompasses a scientific network of academic partners across the world (USA, Canada, Brazil, Africa, Australia), linked to a network of major oil and gas operators and contractors. The project centres around the opportunistic use of ROVs (Remotely Operated Vehicles) in operational settings during periods of stand-by time. The project also aims to maximise the scientific benefit of environmental data collected as part of routine offshore operations and environmental surveys. Through access to ROVs and such environmental data scientists at NOCS and from the wider SERPENT partnership aim to improve the scientific understanding of the deep-sea's biodiversity in all its aspects. This document provides a history of SERPENT missions from its beginnings in July 2002 to the end of 2006 and detailed cruise reports for the missions where they are available.

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)0.098
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0980.015
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0080.005
Science and technology studies0.0020.005
Scholarly communication0.0030.001
Open science0.0110.026
Research integrity0.0010.016
Insufficient payload (model declined to judge)0.0850.264

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 head0.161
GPT teacher head0.398
Teacher spread0.237 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2007
Admission routes1
Has abstractyes

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Same venueNERC Open Research Archive (Natural Environment Research Council)French-language works237,207