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Record W2326343714 · doi:10.15766/mep_2374-8265.7976

PedsCases - A Learning Module for Evaluation of Pediatric Short Stature and Delayed Puberty for Medical Students

2010· article· en· W2326343714 on OpenAlexaffabout
Peter MacPherson, Seth D. Marks, Robert Couch

Bibliographic record

VenueMedEdPORTAL · 2010
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedical educationCurriculumMedicineModalitiesPediatricsPsychologyPedagogy

Abstract

fetched live from OpenAlex

Abstract This resource is a podcast-based learning module that reviews an approach to the evaluation of short stature for medical students. In addition, a multistep case outlines a thorough approach to evaluating delayed puberty in a pediatric patient. This resource is a part of PedsCases, a comprehensive web-based educational series that focuses on the core objectives of undergraduate pediatric education with extensive student involvement. PedsCases was created for and by medical students to provide an opportunity for active self-directed learning in pediatrics. The learning modalities available include questions, flash card–type quizzes, multistep clinical cases, and podcasts. PedsCases has been integrated into the third-year undergraduate pediatric medical education curriculum at the University of Alberta. It is one of the main sources recommended to students to assist in covering the core objectives of the clinical pediatric rotation and in preparing for the final examinations.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.080
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0800.018

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 head0.035
GPT teacher head0.396
Teacher spread0.361 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations1
Published2010
Admission routes2
Has abstractyes

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Same venueMedEdPORTALSame topicChildhood Cancer Survivors' Quality of LifeFrench-language works237,207