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Record W2572881734

North-Sea-Weed-Chain: sustainable seaweed from the North Sea; an exploration of the value chain

2016· article· en· W2572881734 on OpenAlexaff
F.C. Groenendijk, P. Bikker, R. Blaauw, W.A. Brandenburg, S.W.K. van den Burg, P.F.H. Harmsen, R.G. Jak, Pauline Kamermans, M.M. van Krimpen, H.H.T. Prins, M. Stuiver, A.K. van der Werf, Mathieu Scholl, J. Wald

Bibliographic record

VenueSocio-Environmental Systems Modeling · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsImpact
Fundersnot available
KeywordsWeedForestryGeographyHumanitiesArtEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Zeewier is een potentieel belangrijke voedselbron en grote duurzame koolstofbron voor de biobased economy. Met de groeiende wereldbevolking is het noodzakelijk om voor ons voedsel meer te kijken naar de zee als ‘landbouwgebied’. Boeren op zee is een grote uitdaging. Het vereist grote investeringen in infrastructuur. Voordat ondernemers hierin kunnen investeren moeten realistische vooruitzichten zijn op kweekmogelijkheden en winstgevende eindproducten. Dit project had tot doel de verschillende schakels in de keten van zeewierproductie tot vermarkting tegen het licht te houden. Duurzaamheid van de productie is hierbij leidend geweest.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.191
Teacher spread0.170 · 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 designQualitative
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

Citations13
Published2016
Admission routes1
Has abstractyes

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