Comparative Study of IQ-Ultra and Finn Chambers Test Methodologies in Detecting 10 Common Standard Allergens that Cause Allergic Contact Dermatitis
Bibliographic record
Abstract
BACKGROUND: Patch testing is routinely used in contact dermatitis clinics because it is the gold standard for the evaluation of potential allergic contact dermatitis. OBJECTIVE: The study was undertaken to evaluate possible differences in reactivity between the Finn Chamber and IQ-Ultra patch-testing methodologies. METHODS: Patients were patch-tested simultaneously with the Finn Chamber and IQ-Ultra patch tests. Ten standard allergens set by the North American Contact Dermatitis Group were used for both techniques. RESULTS: Both patch tests had a significant agreement in detecting all of the allergens. An "almost perfect agreement" was noted for ethylenediamine dihydrochloride, quaternium-15, mercapto mix, black rubber mix, balsam of Peru, and nickel sulfate; "substantial agreement" for formaldehyde, bisphenol A epoxy resin, and 4-tert-butylphenol formaldehyde resin; and "moderate agreement" for potassium dichromate. CONCLUSION: The Finn Chamber and IQ-Ultra patch tests had a good agreement in the detection of the 10 standard allergens that were tested.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".