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Cognitive developmental influences on the ability of preschool-aged children to self-report their pain intensity

2015· article· en· W2330921938 on OpenAlexaffabout
Jenny Yun‐Chen Chan, Carl L. von Baeyer

Bibliographic record

VenuePain · 2015
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsResearch ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsCognitionPsychologyCognitive developmentLibrary scienceGerontologyMedicineFamily medicineDevelopmental psychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

aInstitute of Child Development, University of Minnesota-Twin Cities, Minneapolis, MN, USA Departments of bClinical Health Psychology, and cPediatrics and Child Health, Faculty of Medicine, University of Manitoba, Winnipeg, MB, Canada Corresponding author. Address: 203—147 Provencher Blvd, Winnipeg, MB R2H 0C9, Canada. Tel.: +1 204 235 1314. E-mail address: [email protected] (C. L. von Baeyer). Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.painjournalonline.com). Received May 22, 2015 Received in revised form August 30, 2015 Accepted October 30, 2015

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)0.021
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.019
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 head0.025
GPT teacher head0.275
Teacher spread0.249 · 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.

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

Citations51
Published2015
Admission routes2
Has abstractyes

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