On the trigeminal percept of androstenone and its implications on the rate of specific anosmia
Bibliographic record
Abstract
Specific anosmia is a term that describes an inability to perceive a particular odorant in the context of an otherwise normal olfactory acuity. The most common example, for the odor of androstenone, has been ascribed a prevalence ranging from 2 to 45%. In two experiments we sought to determine whether this wide range could be explained by the difference in steroid concentrations used, and by the degree to which the trigeminal system contributes to perception of androstenone. Experiment 1 demonstrated that high concentrations of androstenone stimulated the trigeminal system, as indicated by electrophysiological recordings. Experiment 2 demonstrated that conscious detection of androstenone is possible based solely on the trigeminal system. Interestingly, detection seems to interact with olfactory acuity in that subjects with a low olfactory sensitivity to androstenone were better able to detect its trigeminal component. The agreement between conscious experience and behavioral discrimination was not well calibrated, in that subjects demonstrated a clear overconfidence in their abilities. Altogether, the current study suggests that androstenone is an odorant that produces a concentration-dependent degree of trigeminal stimulation. This trigeminal component explains the diversity of the reported prevalence of specific anosmia for androstenone and might have implications on future use of specific anosmia as a tool to understand odor processing.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".