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Component Engineering for an Implantable System

2004· article· en· W1984528838 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

VenueArtificial Organs · 2004
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsComponent (thermodynamics)Artificial heartMiniaturizationEngineeringControl systemReciprocating motionControl engineeringComputer scienceElectrical engineeringMechanical engineeringMedicineSurgery

Abstract

fetched live from OpenAlex

Component engineering is important for the development of implantable-type rotary blood pumps (RP). The authors are conducting elementary development of an implantable artificial heart. A sensor system detects information in the living body. An automatic control system performs the drive control. Energy is provided by a transcutaneous energy transmission system (TETS). Various artificial hearts are being created. Miniaturization resulting from an increase in operating frequency is planned. A vibrating flow pump (VFP) has a reduced size of pumping chamber because of the high-speed reciprocating movement. Undulation pump ventricular assist devices (UPVAD) are small, lightweight rotary pumps. VFPs are useful in the medical treatment of multiple organ failure (MOF). UPVADs are planned to be permanent-use RPs. The purposes of these two artificial hearts differ, although they have a common component. The authors are developing TETS by using amorphous fibers, making efficient power transmission possible. Control information input from a micro or nano sensor is realized. A control algorithm has been developed and baroreflex control has been successful. Artificial heart development, fully exploiting component engineering, continues.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.594

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 communication0.0000.000
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 head0.216
Teacher spread0.195 · 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