MétaCan
Menu
Back to cohort
Record W2138108986 · doi:10.1002/bit.24562

Improving piezoelectric cell printing accuracy and reliability through neutral buoyancy of suspensions

2012· article· en· W2138108986 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

VenueBiotechnology and Bioengineering · 2012
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMicrofluidicsMaterials scienceNozzleReproducibilityDrop (telecommunication)PiezoelectricityFicollSuspension (topology)RepeatabilityNeutral buoyancyNanotechnologyBuoyancyInkwellChromatographyChemistryComposite materialMechanical engineeringEngineeringMechanics

Abstract

fetched live from OpenAlex

The sedimentation and aggregation of cells within inkjet printing systems has been hypothesized to negatively impact printer performance. The purpose of this study was to investigate this influence through the use of neutral buoyancy. Ficoll PM400 was used to create neutrally buoyant MCF-7 breast cancer cell suspensions, which were ejected using a piezoelectric drop-on-demand inkjet printing system. It was found that using a neutrally buoyant suspension greatly increased the reproducibility of consistent cell counts, and eliminated nozzle clogging. Moreover, the use of Ficoll PM400 was shown to not affect cellular viability. This is the first demonstration of such scale and accuracy achieved using a piezoelectric inkjet printing system for cellular dispensing.

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 score0.062
Threshold uncertainty score0.669

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 integrity0.0000.001
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 head0.010
GPT teacher head0.235
Teacher spread0.225 · 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