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{
    "pk": 21535,
    "title": "Combining individuating and context-general cues in lie detection",
    "subtitle": null,
    "abstract": "To date, no account of lie-truth judgement formation has been capable of explaining how core cognitive mechanisms such as memory encoding and retrieval are employed to reach a judgement of either truth or lie. One account, the Adaptive Lie Detector theory (ALIED: Street, Bischof, Vadillo, & Kingstone, 2016) is sufficiently well defined that its assumptions may be implemented in a computational model. In this paper we describe our attempt to ground ALIED in the representations and mechanisms of the ACT-R cognitive architecture and then test the model by comparing it to human data from an experiment conducted by Street et al. (2016). The model provides a close fit to the human data and a plausible mechanistic account of how specific and general information are integrated in the formation of truth-lie judgements.",
    "language": null,
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Psychology; Decision making; Learning; Memory; Computational Modeling"
        }
    ],
    "section": "Papers with Oral Presentation",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/0984x748",
    "frozenauthors": [
        {
            "first_name": "David",
            "middle_name": "",
            "last_name": "Peebles",
            "name_suffix": "",
            "institution": "University of Huddersfield",
            "department": ""
        },
        {
            "first_name": "Chris",
            "middle_name": "",
            "last_name": "Street",
            "name_suffix": "",
            "institution": "Keele University",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2024-01-01T18:00:00Z",
    "render_galley": null,
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}