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Record W4296301609 · doi:10.1097/dad.0000000000002252

Unruly Hair with Irregular Cross Sections: Answer

2022· article· en· W4296301609 on OpenAlexaffabout
Nikhil Nair, Katelynn Campbell, Megan S. Evans

Bibliographic record

VenueAmerican Journal of Dermatopathology · 2022
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsSaskatchewan Health Authority
Fundersnot available
KeywordsLibrary scienceMedicineComputer science

Abstract

fetched live from OpenAlex

*University of Arkansas for Medical Sciences, College of Medicine, Little Rock, AR; †Department of Pathology and Laboratory Medicine, Saskatchewan Health Authority, Saskatoon, Saskatchewan, Canada; and ‡Department of Dermatology, University of Arkansas for Medical Sciences, Little Rock, AR. Correspondence: Nikhil Nair, BA, University of Arkansas for Medical Sciences, College of Medicine, 4301 W. Markham Street, Little Rock, AR 72205 (e-mail: [email protected]). The authors declare no conflicts of interest. I confirm that each author acknowledges their participation in conducting the research leading to this manuscript and agrees to its submission to be considered for publication.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.004
GPT teacher head0.250
Teacher spread0.246 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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