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Impediments to Research in Pediatric Dermatology: The Results of a Survey of the Members of the Society for Pediatric Dermatology

2010· article· en· W2151623685 on OpenAlexaff
Elena Pope, Venetia Lo, Amy S. Paller

Bibliographic record

VenuePediatric Dermatology · 2010
Typearticle
Languageen
FieldMedicine
TopicMedicine and Dermatology Studies History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineDermatologyFamily medicine

Abstract

fetched live from OpenAlex

A research task force of the Society for Pediatric Dermatology (SPD) was established to investigate the barriers to expanding research in the field of pediatric dermatology. A survey was designed to address constraints limiting research activities among members of the SPD. A nine-question survey was distributed to SPD members at the annual meeting in 2007. Of the 70 respondents, 99% reported limitations to research activities. Of those, 90% (62/69) cited time constraints as a cause, 71% lack of funding, 38% lack of training, 35% lack of research infrastructure, 10% (7/69) lack of mentoring, and 25% (17/69) cited other reasons. SPD members face many challenges that curtail their bench and clinical research, although time constraints are most common. The high demand for clinic-directed activity and continuing workforce issues in the specialty likely contribute to the time constraints.

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)0.026
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.074
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.354
Teacher spread0.295 · 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.

Study designObservational
DomainIncentives
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

Citations6
Published2010
Admission routes1
Has abstractyes

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