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Record W1970400660 · doi:10.1088/0026-1394/40/2/312

Characterization of a pneumatic differential pressure transfer standard

2003· article· en· W1970400660 on OpenAlex
Nita Dilawar, Deepak Varandani, Amit Bandyopadhyay, A. C. Gupta

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMetrologia · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsTransducerPiston (optics)Pressure sensorPressure measurementStrain gaugeDifferential pressureData acquisitionPneumatic cylinderComputer scienceMechanical engineeringAcousticsElectrical engineeringControl theory (sociology)PhysicsMechanicsEngineeringCylinderOpticsOperating system

Abstract

fetched live from OpenAlex

The paper describes a novel method for the characterization of a pneumatic differential transfer standard in the differential pressure range 0 Pa to 3.5 MPa up to a high line gas pressure of 7.0 MPa. In view of the advances in the field of automated data acquisition systems an effort has been made to incorporate such a system in the conventional pressure measurement, which uses relatively high accuracy piston gauges and the user-friendly digital transducer. The transfer standard used in the present work is a silicon strain gauge transducer, model PMP 4115, made by Druck, with an output voltage range of 0 V to 5 V with a readout unit/power supply DPI 282. The transducer was characterized against the secondary standard, which is a twin pressure balance, Model 5502, made by Desgranges et Huot, France, designated as NPL-8. The characterization was done through an automated data acquisition system using a model 9118HR A/D interface card made by Adlink, as well as the readout unit DPI 282. The uncertainty estimations showed up considerable differences between the two modes of data acquisition. The observed results were further used to generate a regression equation for the estimation of differential pressure at any given line pressure.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.335
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.146
GPT teacher head0.354
Teacher spread0.208 · 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