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Record W2965256246 · doi:10.4018/jcit.2019100103

Internet of Things (IOT)-Enabled Product Monitoring at Steadyserv

2019· article· en· W2965256246 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

VenueJournal of Cases on Information Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsUniversity of FrederictonUniversity of New Brunswick
Fundersnot available
KeywordsInternet of ThingsVendorRadio-frequency identificationCloud computingSoftware deploymentProduct (mathematics)Supply chainComputer scienceIdentification (biology)BusinessTelecommunicationsProcess managementMarketingComputer securitySoftware engineering

Abstract

fetched live from OpenAlex

This qualitative case study features SteadyServ, a beer inventory monitoring solution vendor, and its internet of things (IOT)-based radio frequency identification (RFID)-enabled technology solution. IOT-based information technology systems are powering new business models and innovative cloud-supported solutions addressing use cases in many industries. At this early stage, IOT is taking off in monitoring premises, products, supply chains, and customers. Content analysis of primary and secondary data was used to interpret this firm's RFID-enabled IOT solution's deployment at the firm's customer sites. Two theoretical frameworks were used in the attempt to understand the IT solution experiences of customer firms: socio-technical systems theory and affordances theory.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.008
GPT teacher head0.222
Teacher spread0.215 · 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