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Record W2502816651 · doi:10.1201/b21483

Science, Information, and Policy Interface for Effective Coastal and Ocean Management

2016· book· en· W2502816651 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
FundersDivision of Human Resource DevelopmentMinistry of Statistics and Programme Implementation, Government of IndiaMinistry of Women and Child DevelopmentMinistry of Health and Family WelfareMinistry of Education, IndiaVetenskapsrådetSuomen KulttuurirahastoLobachevsky State University of Nizhny NovgorodIndian Council of Medical ResearchRoyal College of ArtHome OfficeUniversity of OxfordAcademy of FinlandUniversity of CambridgeWorld Health OrganizationInternational Fine Particle Research InstituteUniversity of OklahomaUnited Nations High Commissioner for RefugeesUniversity of MelbourneHarvard UniversityEuropean CommissionHelsingin YliopistoBernard van Leer FoundationUniversity of ChicagoMcGill UniversityUniversity of MinnesotaNational Institute of Public Cooperation and Child DevelopmentPrinceton UniversityTampereen YliopistoUNICEFYale University
KeywordsInterface (matter)OceanographyInformation managementBusinessEnvironmental resource managementEnvironmental scienceGeographyKnowledge managementComputer scienceGeologyMeteorology

Abstract

fetched live from OpenAlex

Recent atrocities have insured that terrorism and how to deal with terrorists legally and politically has been the subject of much discussion and debate on the international stage. This book presents a study of changes in the legal treatment of those perpetrating crimes of a political character over several decades. It most centrally deals with the political offence exception and how it has come to have changed. The book looks at this change from an international perspective with a particular focus on the United States. Interdisciplinary in approach, it examines the fields of terrorism and political crime from legal, political science and criminological perspectives. It will be of interest to a broad range of academics and researchers, as well as to policy-makers involved in creating new anti-terrorist policies.

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)0.002
metaresearch head score (Gemma)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.046
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0110.008
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0460.008

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 head0.002
GPT teacher head0.209
Teacher spread0.207 · 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
GenreOther

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

Citations10
Published2016
Admission routes1
Has abstractyes

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Same topicCoastal and Marine ManagementFrench-language works237,207