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Record W2619868766 · doi:10.1002/dev.21523

The feasibility of salivary sample collection in an international pediatric cohort: The the TEDDY study

2017· article· en· W2619868766 on OpenAlexfundno aff
Roswith Roth, Judith Baxter, Kendra Vehik, Diane Hopkins, Michael Killian, Patricia Gesualdo, Jessica Melin, Barbara Simell, Elisabeth Strauss, Åke Lernmark, Suzanne Bennett Johnson

Bibliographic record

VenueDevelopmental Psychobiology · 2017
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Child Health and Human DevelopmentNational Institute of Environmental Health SciencesNational Institute of Allergy and Infectious DiseasesJuvenile Diabetes Research Foundation CanadaChinese Center for Disease Control and PreventionNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsSalivaProtocol (science)PopulationMedicineCohortData collectionSample (material)Environmental healthInternal medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

Saliva offers a relatively noninvasive method for measuring analytes such as cortisol, holding particular promise for use in pediatric populations on a large scale if a rigorous collection protocol is feasible in diverse settings. The Environmental Determinants of Diabetes in the Young study protocol, conducted in centers in the United States, Sweden, Finland, and Germany, used salivary collection to assess cortisol level as a physiologic marker of stress. Saliva was collected using Sorbettes from subjects at 3.5, 4.5, and 5.5 years of age. Parents collected a morning sample, and staff collected pre- and post-blood draw samples. Feasibility was assessed based on protocol completion, adherence with instructions, factors affecting adherence, and sufficiency of saliva sample for cortisol determination. Collection of saliva samples in a diverse pediatric population is feasible. Establishing non-invasive and acceptable methods for collecting physiological parameters of stress will allow better exploration of determinants of health in this important population.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.097
GPT teacher head0.387
Teacher spread0.290 · 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 designObservational
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

Citations13
Published2017
Admission routes1
Has abstractyes

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