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Record W3038229173 · doi:10.1017/s1431927600031068

A Comparison of the Elemental Concentrations Obtained using X-ray Microanalysis of Bulk Cryofractured and Ultrathin Cryosectioned Mucus Layer of the Airway Surface Liquid in Mouse Trachea

2001· article· en· W3038229173 on OpenAlexaff
Cameron Ackerley, Geraldine Kent, Yew-Meng Heng, A Tilups, Lukas Becker

Bibliographic record

VenueMicroscopy and Microanalysis · 2001
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsHospital for Sick ChildrenSystems, Applications & Products in Data Processing (Canada)
Fundersnot available
KeywordsMucusLayer (electronics)WettingAirwayMicroanalysisMaterials scienceSurface layerRespiratory systemBiophysicsChemistryAnatomyComposite materialBiologyMedicine

Abstract

fetched live from OpenAlex

Abstract The airways are lined with a thin film consisting of two layers. A watery layer, the airway surface liquid (ASL) surrounds the cilia and its major function is to serve as a medium for ciliary boating of mucus out of the respiratory system. The other layer is a viscous mucus layer consisting mainly of airway cellular secretions and cellular debris. The composition and effects of altered concentrations of the constitutive elements in the ASL and mucus layer remain a mystery. in human patients, attempts have been made to determine the composition of these layers by sampling with a filter paper by touching it to the mucosa and wetting it by capillary action. This material was then removed from the filter paper and quantitative analyses using energy dispersive x-ray spectrometry (EDS) and a Hall’s thin film correction routine performed on the residue. Although differences were detected between normal and pathological material, these results did not reflect the composition of the individual layers but an average of both. Attempts have been made to determine the elemental composition of these layers in intact and in cultured rabbit trachea, bovine trachea and hamster trachea.

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 score0.143
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.310
Teacher spread0.289 · 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

Citations0
Published2001
Admission routes1
Has abstractyes

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