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Record W1964457043 · doi:10.1039/b718187f

One-step thickness shear mode acoustic assay for plasminogen activators

2008· article· en· W1964457043 on OpenAlexafffund
Mirnader Ghazali, Gordon L. Hayward

Bibliographic record

VenueThe Analyst · 2008
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRelative standard deviationFibrinogenFibrinChemistryMaterials scienceShear (geology)Plasminogen activatorTissue plasminogen activatorAnalytical Chemistry (journal)ShakerDissolutionStandard deviationChromatographyComposite materialAcousticsDetection limitBiochemistryBiologyImmunologyMedicineInternal medicineMathematics

Abstract

fetched live from OpenAlex

A new procedure is presented for the measurement of plasminogen activators using a thickness shear mode sensor and a modified version of the fibrin plate assay at the micro-scale. Separate, well-mixed solutions of the substrates fibrinogen and plasminogen, and enzymes thrombin and the plasminogen activator sample were mixed together and placed on the sensor surface. The temperature and evaporation were controlled during the assay. The clot dissolution time correlated well with the quantity of the plasminogen activator in the sample. The average relative standard deviation was 12.5%.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score0.601

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 head0.026
GPT teacher head0.242
Teacher spread0.216 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2008
Admission routes2
Has abstractyes

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