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Patient Performed Reading of a Phototest - A Reliable Method?

2012· article· en· W2112755796 on OpenAlexvenueno aff
L. Thorslund, Magnus Falk

Bibliographic record

VenueJournal of Analytical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineReading (process)PopulationClinical PracticeReliability (semiconductor)Primary careCohen's kappaTest (biology)DermatologyFamily medicineEnvironmental healthStatistics

Abstract

fetched live from OpenAlex

In various situations, in clinical practice or for prevention purposes directed at skin cancer, a broadened use of phototesting to estimate individual skin UV-sensitivity may be warranted. The aim of the present study was to investigate, in a primary health care population, the reliability of patient performed reading of a UVB phototest, when compared to the reading of a trained physician. Thirty-two subjects, all patients recruited in a primary health care population, underwent a UVB phototest, applied on the forearm. Test reading was performed after 24 hours, by the subjects themselves, by counting the number of erythemal reactions (0-6) detectable, and immediately after this, an independent control reading performed by a doctor was also done. The results showed a 72% absolute agreement between the subjects' readings and the control readings, and with a weighted kappa-value of 0.78 (95 CI: 0.64 - 0.91), i.e. corresponding to "substantial agreement". In conclusion, patient performed self-reading of a UVB phototest appears to be a fairly reliable method for estimation of individual skin UV-sensitivity, when compared to the reading of a trained observer. The finding opens up for a broadened use of phototesting in clinical practice and for preventive initiatives aiming at identifying at-risk individuals and reducing sun exposure.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.037
GPT teacher head0.382
Teacher spread0.346 · 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 designNot applicable
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

Citations3
Published2012
Admission routes1
Has abstractyes

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