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Record W2170394279 · doi:10.1109/imtc.2010.5488120

Design and calibration of a flow-following sensor prototype for operation up to 175°C

2010· article· en· W2170394279 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

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransportation Systems and Infrastructure
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsKraft paperKraft processCalibrationProcess engineeringPulp (tooth)Temperature measurementAutomotive engineeringFlow sensorComputer scienceEnvironmental sciencePulp and paper industryEngineeringAcousticsMathematics

Abstract

fetched live from OpenAlex

In kraft pulping process, plup is produced by cooking wood chips at high temperature with chemical liquors in a kraft pulp digester. The temperature uniformity inside the digester is difficult to determine precisely due to the digester size and complexity. This paper presents the design and calibration of a prototype flow-following sensor that measures and records temperature at regular time intervals inside a kraft pulp digester. To make a large-scale deployment economical, the sensor consists of mainstream automotive-grade electronic components. Experimental results show that the prototype can operate reliably at 175°C for 2 hours continuously and over 50 hours cumulatively. After calibration, the accuracy of the temperature measurement is better than ±0.51°C while the overall time accuracy is better than ±141s for a typical 8 hour long digester run.

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: none
Teacher disagreement score0.864
Threshold uncertainty score0.285

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 communication0.0000.001
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 head0.021
GPT teacher head0.245
Teacher spread0.223 · 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