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Record W2521732343 · doi:10.1515/pthp-2016-0008

Prospective Descriptive Study of RFID Tag Detection Rates based on Various Exploratory Scenarios Aimed at Identifying Optimal Conditions of Use

2016· article· en· W2521732343 on OpenAlex
Camille Petit, Maxime Bergeron, Suzanne Atkinson, Denis Lebel, Jean‐François Bussières

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePharmaceutical Technology in Hospital Pharmacy · 2016
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersAssociation des pharmaciens du CanadaUniversité de MontréalMcGill UniversityUniversité Laval
KeywordsTraceabilityRadio-frequency identificationComputer scienceReading (process)Identification (biology)Real-time computingComputer security

Abstract

fetched live from OpenAlex

Abstract Objective The main objective is to evaluate RFID tags detection rates using various exploratory scenarios in order to identify optimal conditions of use. The secondary objective is to evaluate RFID tags detection rates based on a real-life scenario involving a cardiorespiratory resuscitation drug tray used within our institution in order to identify optimal conditions of use. Background The traceability of goods has been a subject of interest for more than a century. Traceability makes it possible to locate goods at every step in the chain from production through to disposal. Just as with other Automatic Identification and Data Capture technologies, radio frequency identification (RFID) is used to increase the traceability of objects. Results Seven variables that could influence RFID tags detection rates were evaluated in eight exploratory scenarios. Optimal detection parameters allowing to a 100 % detection rate were identified: a 10-second reading time; a reading distance of 10 cm; parallel orientation of reader-antenna and at least two back and forth readings for a total of 6 sec were required for optimal reading. Detection rates decreased after 100 RFID tags and it were not affected by the shape of the RFID tags. Reader-antenna and RFID tag interferences resulted from aluminum paper or RFID tags that touched one another. RFID tag detection rates obtained per operator were similar. Regarding real-life scenarios, detection rates increased with reading times and a plateau effect was observed after 10 sec. Undetected elements varied and non-detection was almost always related to the proximity of two RFID tags rather than the nature of the items read. Conclusion To our knowledge, this is the first prospective descriptive study that compares RFID tag detection rates based on various exploratory scenarios in order to identify optimal conditions of use. Such results can be used to develop a software application supporting drug replenishing through RFID in the drug use process.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.330
Teacher spread0.292 · 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