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Record W4210758058 · doi:10.1109/mim.2022.9693460

Guest Editorial

2022· editorial· en· W4210758058 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

VenueIEEE Instrumentation & Measurement Magazine · 2022
Typeeditorial
Languageen
FieldComputer Science
TopicIoT and Edge/Fog Computing
Canadian institutionsCarleton University
Fundersnot available
KeywordsIntelligent sensorComputer scienceControl (management)Everyday lifeIntelligent agentComputer securityHuman–computer interactionIntelligent controlInternet privacyWireless sensor networkArtificial intelligenceComputer network

Abstract

fetched live from OpenAlex

We currently live in a world full of intelligent sensors. These intelligent sensors almost control our lives as our everyday activities now depend on the data provided by such sensors. For instance, our smart devices monitor our heart rate, our daily activities, and our sleep. They alert us to conduct various activities and connect us to either health care providers when there are medical alerts. There now exist self-driving cars which are able to make intelligent decisions like human beings while driving on the road. Thus, devices and machines are not only becoming intelligent but are also becoming autonomous.

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)0.003
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.025
GPT teacher head0.261
Teacher spread0.235 · 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