Aluminum—Allergen of the Year 2022
Bibliographic record
Abstract
ABSTRACT: Exposure to elemental aluminum and its salts is unavoidable. Aluminum as a metal is present in transport, construction, packaging, and electronic equipment. Aluminum salts are present in consumer products, food items and drinking water, vaccines, drugs, and antiperspirants. Aluminum in vaccines and preparations for allergen-specific immunotherapy are the major sensitization sources. The predominent clinical manifestations of aluminum allergy are pruritic subcutaneous nodules and eczematous dermatitis. Patch testing shall be performed with aluminum chloride hexahydrate (ACH) in petrolatum. The preparation with ACH 10% detects substantially more aluminum allergy than ACH 2%. A patch test with elemental aluminum, for example, an empty Finn Chamber, is only positive when there is a strong aluminum allergy. A patch test reading should be performed 1 week after the application so as not to miss 15% to 20% of aluminum allergy. Aluminum should be included in any baseline patch test series for children and investigated for a possible inclusion in baseline series for adults. Aluminum test chambers can interfere with the testing resulting in both false-negative and false-positive patch test reactions to nonaluminum contact sensitizers.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".