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Record W1995396863 · doi:10.1042/bj20141083

NTBI unveiled by chelatable fluorescent beads

2014· letter· en· W1995396863 on OpenAlexafffund
Giada Sebastiani, Kostas Pantopoulos

Bibliographic record

VenueBiochemical Journal · 2014
Typeletter
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsJewish General HospitalMcGill UniversityRoyal Victoria HospitalRoyal Victoria Regional Health Centre
FundersCanadian Institutes of Health Research
KeywordsTransferrinFluorescenceMedicineChemistryNanotechnologyBiochemistryMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Non-transferrin-bound iron (NTBI) emerges in plasma of patients with systemic iron overload, but has also been documented in further pathological conditions. Quantification of NTBI can be useful for diagnosis and management of these disorders. However, currently available detection methods are tedious and often inaccurate, hampering wide applicability. In this issue of the Biochemical Journal, Ma et al. report the development of a novel assay for NTBI measurement, based on an iron-sensitive fluorescent probe that is linked to magnetic beads. The approach offers several advantages over existing technology and may bring NTBI assessment closer to the clinic.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0020.003

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 head0.243
Teacher spread0.233 · 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

Citations2
Published2014
Admission routes2
Has abstractyes

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