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Record W2161448654 · doi:10.1109/iembs.2004.1403433

Precision control of eluted activity from a Sr/Rb generator for cardiac positron emission tomography

2005· article· en· W2161448654 on OpenAlexaff
Ran Klein, Andy Adler, Rob Beanlands, Robert A. deKemp

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsElutionPositron emission tomographyRepeatabilityGenerator (circuit theory)ChemistryMaterials scienceControl theory (sociology)Analytical Chemistry (journal)ChromatographyBiomedical engineeringNuclear medicinePhysicsComputer scienceEngineeringMedicine

Abstract

fetched live from OpenAlex

A rubidium-82 (/sup 82/Rb) elution system is described for use with clinical positron emission tomography. The system is self-calibrating with 1.4% repeatability, independent of generator activity and elution flow rate. Saline flow is switched between a /sup 82/Sr//sup 82/Rb generator and a bypass line to achieve a constant activity elution of /sup 82/Rb. In the present study, pulse width modulation (PWM) of a solenoid valve is compared to simple threshold control as a means to simulate a proportional valve. A predictive-corrective control algorithm is developed which produces a constant activity elution within the constraints of long feedback delay and short elution time. Accurate constant-activity elutions of 10-70% of the total generator activity were demonstrated using the threshold comparison control. The adaptive-corrective control of the PWM valve provided a substantial improvement in precision of the steady-state output.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.306
Teacher spread0.295 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2005
Admission routes1
Has abstractyes

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