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Record W6948795086 · doi:10.5278/ojs.td.v1i1.6020

National Strategisk Analyse i politiet

2020· article· da· W6948795086 on OpenAlexaboutno aff

Bibliographic record

VenueAalborg University Library · 2020
Typearticle
Languageda
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsNational libraryGovernment (linguistics)Quarter (Canadian coin)

Abstract

fetched live from OpenAlex

Siden 2015 har Rigspolitiet hvert år udarbejdet en national Strategisk Analyse, som behandler udviklingen inden for alle typer af kriminalitet, trafiksikkerhed og beredskab. Trafiksikkerhedsafsnittet består dels af en analyse af udviklingen i uheldsstatistikken og dels af en analyse af udviklingen i ”politisager” inden for spirituskørsel, hastighedsovertrædelser og distraktion. Uheldsdata dækker perioden 2009 til 2015 mens politidata går frem til 2016. På Trafikdagene vil uheldsdata fra 2016 være indarbejdet i præsentationen. Med baggrund i den strategiske analyse har politiet udarbejdet en national operativ strategi, som ligeledes bliver præsenteret på Trafikdagene.

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)0.008
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.081
Threshold uncertainty score0.271

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0040.003
Scholarly communication0.0120.004
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0810.015

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 head0.014
GPT teacher head0.172
Teacher spread0.158 · 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 designObservational
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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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