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Record W4244119433 · doi:10.5771/9783748921011-131

Non-State Actors, Piracy and Threats to Global Shipping

2021· book-chapter· en· W4244119433 on OpenAlexfundno aff
Dirk Siebels

Bibliographic record

VenueNomos Verlagsgesellschaft mbH & Co. KG eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMaritime Security and History
Canadian institutionsnot available
FundersUniversität RostockUniversität OsnabrückKarl-Franzens-Universität GrazAnadolu ÜniversitesiMcMaster University
KeywordsState (computer science)Computer securityBusinessInternational tradeComputer science

Abstract

fetched live from OpenAlex

agb merging will see a greater demand for sound allied maritime strategy, and the understanding thereof. EpilogueThe study of sea power theory and practice cannot be left confined to the disciples of Mahan or Corbett, or to the classrooms at the naval academies.The maritime domain affects us all, and bridging the gap between history and policy-as exemplified in the events and publications of the ISPK's Center for Maritime Strategy & Security-will go a long way to understanding many contemporary opportunities and shortfalls when it comes to the sea.My sincere gratitude also goes out to everyone who contributed to this book; in particular the 20 authors and the two editors.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.008
Scholarly communication0.0050.004
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.032
GPT teacher head0.305
Teacher spread0.273 · 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 designQualitative
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

Citations0
Published2021
Admission routes1
Has abstractyes

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