MétaCan
Menu
Back to cohort
Record W4387679682 · doi:10.5771/9783748900320-59

Nutzung von Live-Positionsdaten im Rahmen von längerfristigen Observationen und bei der Fahndung nach Diebesgut im Vergleich

2023· book-chapter· de· W4387679682 on OpenAlex
Jessica Kraus, Jan Fährmann

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNomos Verlagsgesellschaft mbH & Co. KG eBooks · 2023
Typebook-chapter
Languagede
FieldSocial Sciences
TopicCriminal Law and Policy
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsPolitical scienceArt

Abstract

fetched live from OpenAlex

Wie bereits dargelegt, nutzt die Polizei bereits Positionsdaten im Ermittlungsverfahren, insbesondere bei der Observation. 3 Mithin verfgt die Polizei ber Erfahrungswissen hinsichtlich des Einsatzes von Ortungstechnologie. Daher stellen sich die Fragen, welche Rckschlsse aus diesen Erkenntnissen hinsichtlich der Live-Ortung von Diebesgut gezogen werden knnen und inwieweit das Erfahrungswissen aus der Observation auf das Auffinden von Diebesgut bertragen werden kann? Zur Beantwortung dieser Fragen sind die beiden Manahmen aus einer kriminalistischen und polizeitaktischen Perspektive heraus miteinander zu vergleichen. Auf den Gemeinsamkeiten sowie den Unterschieden aufbauend werden Anforderungen an die Ortungstechnik zur Diebstahlsaufklrung formuliert. Dabei werden auch der Einbau und die Einsatzbereitschaft der Ortungstechnologie, Qualittsmerkmale der GPS-Module sowie die Akkulaufzeiten

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0050.002
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.026

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 head0.076
GPT teacher head0.343
Teacher spread0.267 · 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