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Miriam A. Stocks

Observed names: M. A. Stocks, M. Stocks, M.A. STOCKS, M.A. Stocks, Miriam Stocks
Observed institution: University of Auckland
ORCID: 0000-0002-4535-4131
Observed ORCID: 0000-0002-4535-4131
OpenAlex ID: A5009923135
Cognitive decision strategies adopted by trained judges in reminder difference tests when tasting yoghurt, mayonnaise, and ice tea
2013 · Miriam A. Stocks, Danielle van Hout, et al. · Food Quality and Preference · 21
Cognitive Decision Strategies Adopted in Reminder Tasks by Trained Judges When Discriminating Aqueous Solutions Differing in the Concentration of Citric Acid
2013 · Miriam A. Stocks, Danielle van Hout, et al. · Journal of Sensory Studies · 19
The single interval adjustment matrix (SIAM) yes–no task: an empirical assessment using auditory and gustatory stimuli
2011 · Daniel Shepherd, Michael J. Hautus, et al. · Attention Perception & Psychophysics · 17
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The Single Interval Adjustment Matrix (siam) Yes-no Task Applied to the Measurement of Sucrose Thresholds
2010 · M.J. HAUTUS, M.A. STOCKS, et al. · Journal of Sensory Studies · 9
Observed discriminability is more variable than predicted by signal detection theory
2019 · M.J. Hautus, D. van Hout, et al. · Food Quality and Preference · 8
Cognitive decision strategies adopted by consumers in reminder difference tests: Influence of the authenticity test
2017 · M. Stocks, D. Shepherd, et al. · Food Research International · 8
Variation of d′ estimates in two versions of the A‐Not A task
2018 · M. J. Hautus, D. van Hout, et al. · Journal of Sensory Studies · 6
The observed variance of dʹ estimates compared across the 2-AFCR, Triangle, and Tetrad tasks
2022 · M.J. Hautus, D. van Hout, et al. · Food Quality and Preference · 3
Cognitive Decision Strategies Adopted by Trained Judges and Consumers in Reminder Tasks
2014 · Miriam A. Stocks · ResearchSpace (University of Auckland) · 2
Assessing the Single Interval Adjustment Matrix Yes-no Task
· Daniel Shepherd, Michael J. Hautus, et al.
Works count: 10
Citation count: 93
H-index: 6
I10-index: 3
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