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Record W2768501536 · doi:10.1049/pbhe010e_ch9

AALaaS/ELEaaS platforms

2017· book-chapter· en· W2768501536 on OpenAlex

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

VenueIET eBooks · 2017
Typebook-chapter
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This chapter presents a generic `ambient assisted living as a service'/`enhanced living environment as a service' platform. Multiple platform elements are described by taking into account layered hierarchical models, horizontally and vertically planning models as well as models with planes. The main goal of the work is to identify the important platform parts, classify the existing models, and create a framework that will allow further protocols and services classification. The chapter starts with a presentation of the end-user requirements, continues with the analysis and design phases, and ends with a possible implementation of the platform as a cloud-based one, aiming to aggregate data from multiple different access and edge technological solutions and islands, and allowing data analysis and mining at the abstract level. This is considered as a driving force for further development of possible business solutions. The work is based on a real-life experience gained within living labs and conducted surveys on the topic.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.954
Threshold uncertainty score1.000

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)0.0000.000

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 head0.023
GPT teacher head0.218
Teacher spread0.194 · 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