Many researchers report that people have an optimistic bias when making predictions, but sometimes cautious realism is found. One resolution is that future thinking has two steps: The desired outcome is imagined first, followed by a sobering reflection on potential difficulty of getting there. Five experiments supported this two-step model (USA and Norway; N = 3213; 10,433 judgments), showing that intuitive predictions are more optimistic than reflective predictions. Participants were randomly assigned to rely on fast intuition under time-pressure or slow reflection after time-delay. In Experiment 1, participants in both conditions thought positive events were more likely to happen to them than to other people and that negative events were less likely, replicating the classic finding of "unrealistic optimism". Crucially, this optimistic tendency was significantly stronger in the intuitive condition. Participants in the intuitive condition also relied more on heuristic problem-solving (CRT). Experiments 2-3 found that participants in the intuitive condition thought they were at lower health risk than participants in the reflective condition. Experiment 4 provided a direct replication, with the additional finding that intuitive predictions were more optimistic only for oneself (and not about the average person). Experiment 5 failed to identify any intuitive difference in perceived reasons for success versus failure, but observed intuitive optimism in binary prediction of a future exercise habit. Experiment 5 also found suggestive evidence for a moderating role of social knowledge: Reflective predictions about oneself became more realistic than intuitive predictions only when the person's base-rate beliefs about other people were fairly accurate.
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http://dx.doi.org/10.1016/j.cognition.2023.105447 | DOI Listing |
Front Chem
November 2024
African Society for Bioinformatics and Computational Biology, Cape Town, South Africa.
Introduction: Homology modeling is a widely used computational technique for predicting the three-dimensional (3D) structures of proteins based on known templates,evolutionary relationships to provide structural insights critical for understanding protein function, interactions, and potential therapeutic targets. However, existing tools often require significant expertise and computational resources, presenting a barrier for many researchers.
Methods: Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline.
Ann Surg Open
December 2024
Tokyo Medical and Dental University, The University of Tokyo, Tokyo, Japan.
Objective: To create and validate nomograms predicting overall survival and recurrence in treatment-naïve rectal cancer (RC) patients who underwent upfront surgery.
Background: Although multidisciplinary treatment is standard for locally advanced RC, understanding surgical efficacy is important for determining indications for perioperative adjuvant therapy.
Methods: RC patients who underwent upfront surgery at the Japanese Society for Cancer of the Colon and Rectum institutions were analyzed.
Ann Surg Open
December 2024
From the Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA.
NPJ Digit Med
December 2024
Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Formative verbal feedback during live surgery is essential for adjusting trainee behavior and accelerating skill acquisition. Despite its importance, understanding optimal feedback is challenging due to the difficulty of capturing and categorizing feedback at scale. We propose a Human-AI Collaborative Refinement Process that uses unsupervised machine learning (Topic Modeling) with human refinement to discover feedback categories from surgical transcripts.
View Article and Find Full Text PDFJ Am Chem Soc
December 2024
Department of Chemistry, Northwestern University, 2145 Sheridan Road, Evanston, Illinois 60208, United States.
For several decades, molecular motor directionality has been rationalized in terms of the free energy of molecular conformations visited before and after the motor takes a step, a so-called power stroke mechanism with analogues in macroscopic engines. Despite theoretical and experimental demonstrations of its flaws, the power stroke language is quite ingrained, and some communities still value power stroke intuition. By building a catalysis-driven motor into simulated numerical experiments, we here systematically report on how directionality responds when the motor is modified accordingly to power stroke intuition.
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