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Record W23855197

The ASEAN Space Organization: Legal Aspects and Feasibility

2009· book· en· W23855197 on OpenAlexfundno aff
Chukeat Noichim

Bibliographic record

Venuenot available
Typebook
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsnot available
FundersJapan Aerospace Exploration AgencyInternational Labour OrganizationU.S. Geological SurveyNational Oceanic and Atmospheric AdministrationNational Commission for Science and TechnologyEuropean CommissionEuropean Organization for the Exploitation of Meteorological SatellitesThailand Graduate Institute of Science and TechnologyOffice of the Civil Service CommissionMae Fah Luang UniversityKementerian Sains, Teknologi dan InovasiUNICEFGeo-Informatics and Space Technology Development AgencyMahanakorn University of TechnologyDeutsches Zentrum für Luft- und RaumfahrtUniversiti Putra MalaysiaUniversiteit LeidenEuropean Space AgencyNanomaterials Microdevices Research Center, Osaka Institute of TechnologyUnited Nations Development ProgrammeAmerican Society for Cell BiologyMcGill UniversityCore Research for Evolutional Science and TechnologyMinistério da Ciência, Tecnologia e InovaçãoNational Aeronautics and Space AdministrationNational Geographic SocietyIndian Space Research OrganisationUnited Nations Educational, Scientific and Cultural OrganizationEuropean University Institute
KeywordsSpace (punctuation)BusinessSustainabilitySustainable developmentOrder (exchange)Outer spaceDeveloping countryDependency (UML)International tradeEconomic growthEconomic systemPolitical scienceEconomicsEngineeringFinanceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Prevention, particularly with regard to older people, has assumed increasing importance in policy in recent years. Prevention not only focuses on diseases but also on the geriatric syndrome and frailty must be crucial for the well-being of older people in the super-aged society. The preventive services aim to sustain independent living among those who are vulnerable and the preventive strategies should be supported by an evidence base that links risk factors with particular conditions and interventions to reduce risk and ameliorate the impact of illness and impairments. However, due to the heterogeneity of this population and a paucity of research on this field, it is difficult to make universal recommendations for the preventive services for the older people.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.740
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.234
Teacher spread0.224 · 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.

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

Citations6
Published2009
Admission routes1
Has abstractyes

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