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Record W7065354185

De veroordeling van Shell tot 45% CO2-reductie in 2030: Over legitimiteit en effectiviteit

2022· article· nl· W7065354185 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2022
Typearticle
Languagenl
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsWindagePneumopericardiumAcquiescence
DOInot available

Abstract

fetched live from OpenAlex

Het opstellen van regels ter bescherming van burgers tegen de schadelijke gevolgen van klimaatverandering is een taak van de wetgever. De civiele rechter heeft op dat terrein in beginsel geen rol. Als echter sprake is van reguleringsfalen en de overheid daardoor tekortschiet in de bescherming van de burger kan dat anders zijn. Nu de doelen uit de Klimaatwet stelselmatig niet worden gehaald kan betoogd worden dat er, zeker op het moment dat de Shell-zaak speelde, sprake was van zo’n reguleringsfalen. Aan het daaropvolgende civiele oordeel kan echter wel de eis worden gesteld dat het feitelijk de mensenrechtelijke positie van de (toekomstige) bewoners van Nederland dient. Want als het optreden van de civiele rechter niet effectief is, corrigeert het dat reguleringsfalen niet. Die effectiviteit is in de Shell-zaak op voorhand niet evident.

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)0.006
metaresearch head score (Gemma)0.011
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: Commentary · Consensus signal: none
Teacher disagreement score0.104
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0070.005
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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
GenreCommentary

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

Citations1
Published2022
Admission routes1
Has abstractyes

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