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Record W6967545960 · doi:10.5281/zenodo.1011128

An Innovative Raft To Boost The Mollusk Farming Industry

2017· article· en· W6967545960 on OpenAlex

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

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldEngineering
TopicMaterials Engineering and Processing
Canadian institutionsResearch & Development Corporation
FundersEuropean Commission
KeywordsContext (archaeology)RaftAgriculturePhase (matter)Production (economics)

Abstract

fetched live from OpenAlex

This document describes the advantages of a new floating raft for the harvest of mussels, oysters and other types of molluscs. The platform is made of an Ultra-High-Performance Fibre Reinforced Concrete (UHPFRC, named in this document UHC) developed by the company Research & Development Concretes SL (RDC in advance) and registered as Formex®. The solution provides advantages in terms of reduction of risks for the employees, environmental impact, competitiveness of the business and potential synergies with other sectors (tourism, weather forecasts, alerts, marine energy), and four of them have been already installed in the context of the H2020 Phase 2 project SELMUS-738777. In this document, many of their advantages are evaluated and a comparison is made with the wooden raft and the longline system in terms of viability of the business.

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 categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0020.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.032
GPT teacher head0.261
Teacher spread0.229 · 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