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Record W3204170537 · doi:10.18174/549531

Agro-Nutri Monitor 2021 - Hoofdrapport : Monitor prijsvorming voedingsmiddelen en analyse belemmeringen voor verduurzaming

2021· report· nl· W3204170537 on OpenAlexaff
Michiel van Galen, W.H.M. Baltussen, Mariel Benus, Koos Gardebroek, Nera Herceglić, R. Hoste, Rico Ihle, Jakob Jager, Bas Janssens, Gerben Jukema, Marcel Kornelis, Marvin Kunz, Katja Logatcheva, E.B. Oosterkamp, Jamal Roskam, H.J. Silvis, Rob Stokkers

Bibliographic record

Venuenot available
Typereport
Languagenl
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsImpact
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Deze Agro-Nutri Monitor is een vervolg op de vorig jaar verschenen eerste monitor. De monitor is in opdracht van de Autoriteit Consument & Markt (ACM) opgesteld door Wageningen Economic Research. Het doel van de monitor is om de prijsvorming in de keten, van boer tot de Nederlandse supermarkt, inzichtelijk te maken en eventuele problemen bij de prijsvorming aan het licht te brengen die verduurzaming van de ketens belemmeren.

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)0.005
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.111
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.014

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 head0.171
GPT teacher head0.452
Teacher spread0.281 · 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
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

Citations7
Published2021
Admission routes1
Has abstractyes

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