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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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations1
Published2022
Admission routes1
Has abstractyes

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