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Record W2419602734 · doi:10.1039/c5lc01532d

Fast, sensitive point of care electrochemical molecular system for point mutation and select agent detection

2016· article· en· W2419602734 on OpenAlexaff
Julius MacLeod, A. C. Nemeth, W. C. Dicke, D. Wang, S. M. Wheeler, James C. Hannis, Galen Collier, Jared J. Drader

Bibliographic record

VenueLab on a Chip · 2016
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsAbbott (Canada)
Fundersnot available
KeywordsPoint of carePoint mutationPoint-of-care testingBattery (electricity)Turnaround timePoint (geometry)CartridgeComputer scienceNanotechnologyMutationEngineeringMedicineChemistryMaterials scienceBiochemistryPhysicsPathologyOperating systemMathematicsGeneMechanical engineering

Abstract

fetched live from OpenAlex

Point of care molecular diagnostics benefits from a portable battery-operated device capable of performing a fast turnaround using reliable inexpensive cartridges. We describe a prototype device for performing a molecular diagnostics test for clinical and biodefense samples in 16 minutes using a prototype capable of an 8 minute PCR reaction, followed by hybridization and detection on an electrochemical microarray based on the i-STAT® system. We used human buccal swabs for hemochromatosis testing including in-device DNA extraction. Additional clinical and biodefense samples included influenza A and bacterial select agents Bacillus anthracis, Yersinia pestis and Francisella tularensis.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.390

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 head0.004
GPT teacher head0.210
Teacher spread0.207 · 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 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

Citations10
Published2016
Admission routes1
Has abstractyes

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