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Thematische Synthese «Akzeptanz» des NFP «Energie»

2019· report· de· W3048390217 on OpenAlexaff
Andreas Balthasar, Frédéric Varone, Daniel Meierhans

Bibliographic record

Venuenot available
Typereport
Languagede
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsWorld Federation of Science Journalists
Fundersnot available
KeywordsChemistryPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Was braucht es, damit die Schweizerinnen und Schweizer ihr Verbrauchsverhalten ändern? Was ist entscheidend für die Unterstützung von Technologien und von Infrastrukturprojekten? Das NFP Energie hat zahlreiche Akzeptanzfaktoren identifiziert. Die Synthese verdichtet diese bis auf die Stufe von konkreten Handlungsempfehlungen.

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)0.010
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: Review · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.007
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.001

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 head0.054
GPT teacher head0.325
Teacher spread0.271 · 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
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

Citations2
Published2019
Admission routes1
Has abstractyes

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