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Record W3139572675 · doi:10.5771/9783748924067

Rechtliche Rahmenbedingungen für die Suche nach einem Endlager für hochradioaktiven Abfall (HAW)

2021· book· en· W3139572675 on OpenAlexaboutno aff
Florian Emanuel

Bibliographic record

VenueNomos Verlagsgesellschaft mbH & Co. KG eBooks · 2021
Typebook
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsnot available
Fundersnot available
KeywordsConstitutionNuclear powerGermanPolitical scienceLawEngineeringGeographyPhysicsNuclear physicsArchaeology

Abstract

fetched live from OpenAlex

Producing nuclear energy inherently produces high active nuclear waste (HAW), which has to be disposed of properly and safely. Disposal of HAW represents an eternal burden of nuclear power – even after the German nuclear phase-out in 2022. This intergenerational challenge is a challenge for many more countries than just Germany. Up to date, in the whole world, there is not one operational disposal facility for HAW. The author deals with the constitutional requirements for the German Site Selection Process and the evaluation criteria derived from the constitution. Based on an international legal comparison, he finally develops recommendations concerning a further legal development of this process. The legal comparison particularly emphasizes Canada, Switzerland and Finland.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.003

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 head0.040
GPT teacher head0.368
Teacher spread0.329 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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