ArticleThe Behavioral and brain sciences2023
Further advancing fast-and-slow theorizing.
Article in The Behavioral and brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Chronic pain is linked to a resting-state neural archetype that optimizes learning from punishments.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The 34 commentaries on the target article span a broad range of interesting issues. I have organized my reply around five major themes that seemed to emerge: Remarks about the generalizability of the empirical findings, links with other models, necessary extensions, the utility of dual-process models, and more specific points. This allows me to clarify possible misconceptions and identify avenues for further advancement.
Identifiers
37462189What OpenQuestion holds
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.