ArticleScientific reports2022
How experts' own inconsistency relates to their confidence and between-expert disagreement.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Confidence judgments, feelings of knowing and judgments of learning: Towards a common framework.Memory & cognition · 2026Article
- Subjective Confidence as a Monitor of the Replicability of the Response.Perspectives on psychological science : a journal of the Association for Psychological Science · 2025Article
- Inconsistencies in rater-based assessments mainly affect borderline candidates: but using simple heuristics might improve pass-fail decisions.Advances in health sciences education : theory and practice · 2024Article
- Boosting wisdom of the crowd for medical image annotation using training performance and task features.Cognitive research: principles and implications · 2024Article
- Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
People routinely rely on experts' advice to guide their decisions. However, experts are known to make inconsistent judgments when judging the same case twice. Previous research on expert inconsistency has largely focused on individual or situational factors; here we focus directly on the cases themselves. First, using a theoretical model, we study how within-expert inconsistency and confidence are related to how strongly experts agree on a case. Second, we empirically test the model's predictions in two real-world datasets with a diagnostic ground truth from follow-up research: diagnosticians rating the same mammograms or images of the lower spine twice. Our modeling and empirical analyses converge on the same novel results: The more experts disagree in their initial decisions about a case (i.e., as consensus decreases), the less confident individual experts are in their initial decision-despite not knowing the level of consensus-and the more likely they are to judge that same case differently when facing it again months later, regardless of whether the expert consensus is correct. Our results suggest the following advice when faced with two conflicting decisions from a single expert: In the absence of more predictive cues, choose the more confident decision.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.