Evidence map›Paper›PMID 38259347›Full record

ArticleArXiv2024

Fast decisions reflect biases, slow decisions do not.

Samantha Linn, Sean D Lawley, Bhargav R Karamched, Zachary P Kilpatrick, Krešimir Josić

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Samantha LinnDepartment of Mathematics, University of Utah, Salt Lake City, Utah, USA.
Sean D LawleyDepartment of Mathematics, University of Utah, Salt Lake City, Utah, USA.
Bhargav R KaramchedDepartment of Mathematics, Florida State University, Tallahassee, Florida 32306, USA.
Zachary P KilpatrickDepartment of Applied Mathematics, University of Colorado Boulder, Boulder, Colorado 80309, USA.
Krešimir JosićDepartment of Mathematics, University of Houston, Houston, Texas 77004, USA.

Funding

Anatomical connectivity and activity in primary visual cortex of mouseRF1MH130416 · NIMH · BAYLOR COLLEGE OF MEDICINE · PI PITKOW, ZACHARY SAMUEL, REIMER, JACOB · 2022 to 2022
$1.3M
Connecting neural circuit architecture and experience-driven probabilistic computationsR01EB029847 · NIBIB · UNIVERSITY OF COLORADO · PI KILPATRICK, ZACHARY PETER · 2020 to 2020
$772k
NIBIB NIH HHS R01 EB029847NIMH NIH HHS RF1 MH130416
6 · The paper itself

Abstract

Decisions are often made by heterogeneous groups of individuals, each with distinct initial biases and access to information of different quality. We show that in large groups of independent agents who accumulate evidence the first to decide are those with the strongest initial biases. Their decisions align with their initial bias, regardless of the underlying truth. In contrast, agents who decide last make decisions as if they were initially unbiased, and hence make better choices. We obtain asymptotic expressions in the large population limit that quantify how agents' initial inclinations shape early decisions. Our analysis shows how bias, information quality, and decision order interact in non-trivial ways to determine the reliability of decisions in a group.

Identifiers

PMID38259347
PMCPMC10802676

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.