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2,827 results for “Decision”
Row data for the experiment: "Clinical, psychosocial and demographic factors affect decisions in SLE people".
<p>These datasets correspond to the article titled: “Clinical, psychosocial and demographic factors affect decisions in SLE people”, which can be found at <a href="https://www.medrxiv.org/content/10.1101/2024.03.25.24304643v1.full.pdf">https://www.medrxiv.org/content/10.1101/2024.03.25.24304643v1.full.pdf</a></p> <p>Analysis scripts, and an explanation of variables, can be found at: <a href="https://github.com/NeuroGenomicsMX/Factors_affecting_decisions_in_SLE">https://github.com/NeuroGenomicsMX/Factors_affecting_decisions_in_SLE</a></p> <p>Abstract</p> <p><span>Neurological and psychiatric manifestations affect most lupus individuals and include depression, anxiety, mood disorders, and cognitive dysfunction. Although there is evidence supporting suboptimal decision-making in lupus and its association with glucocorticoids consumption, it is not clear what variables impact such decisions. The aim of this study is to explore how social, clinical, psychological, and demographic factors impact social and temporal decision-making in people with lupus. Through a within-subjects experimental-design, our participants responded to social, clinical, psychological, and demographic electronic questionnaires. Then, they participated in two behavioral economics experiments: the third-party dictator game, and the delay discounting task. Our results show that hostility, and age are essential predictors of social decisions, whereas obsessive-compulsiveness and anxiety better predict temporal decisions. These variables behave as expected, but anxiety shows unexpected results: most anxious people act patiently and prefer delayed but bigger rewards. Finally, clinical factors are critical decision predictors for social and temporal decisions. When people are in remission, they tend to impose higher punishment on those who violate the social norm, and they also tend to prefer immediate rewards. When taking glucocorticoids, they also prefer immediate rewards, and as the dosage of glucocorticoids intake increases, they tend to impose higher punishment on norm violators. Clinicians, researchers, and practitioners must consider the side effects of glucocorticoids on decision-making.</span></p>
Role of Personal Connections in Shaping Decisions About Private Forest Use in Central Massachusetts 2008
We begin with a simple premise: Social and ecological systems are interconnected in complex ways. Forests are, perhaps, one of the most intriguing examples of this interconnectedness--particularly those in private ownerships. Forested landscapes are essential in maintaining human systems through the provision of multiple ecosystem services that span public (e.g., clean water, nutrient cycling) and private (e.g., fiber, maple syrup, home sites) goods. However, the majority of forestland in the Eastern United States is a mosaic of small landholdings (less than 20 ha) where property management is largely uncoordinated. On such landscapes, decentralized, ownership-centric decision-making defines the mix of ecosystem services provided and the landscape patterns present now and in the future. While somewhat effective for less spatially sensitive ecosystem services (e.g., fiber production), this ownership-centric approach is ill suited to spatially sensitive ones (e.g., water quality) and may, in some cases, be detrimental to them (e.g., habitat fragmentation). Improving the ecological and landscape sensitivity of private forest conservation and management is a major challenge facing researchers, practitioners, and policymakers in sustaining forest ecosystems. Central to unraveling this challenge is a fundamental understanding of how landowners simultaneously fit within their social and bio-physical landscapes. Despite their importance to broader forest sustainability, our collectively understanding of forest landowners has been primarily concerned with individual landowners and/or individual properties. For example, most research surrounding private forest landowners centers on primarily agent-based theories of behavior or decision-making (e.g., rational actor, theory of planned behavior). This perspective is useful in predicting and effecting behavior at broad scales, but lacks the specificity needed to address local landscape concerns and/or opportunities. Other studies
Land Owner Decisions and Consequences in North Central Massachusetts 1950-2009
Landscapes dominated by private ownership experience change as properties change hands, change monetary value, undergo land use conversion, become isolated or lose road access, or are divided and hence smaller in size. The future ecological integrity, connectivity, and function of landscapes dominated by private ownership depend on the speed or frequency with which decisions are made, the kinds of decisions, and their outcomes or consequences. One way to study this human behavior on land is through attitudinal surveys of owners investigating their motivations, beliefs, and values. Another is to pose hypothetical circumstances and query owners about potential response or reactions. Another involves the study of social networks around owners, and determining the extent to which information flows between owners and may influence decisions. We proposed instead to study or monitor decisions made and resulting circumstances, and to establish a long-term framework or network of points at which land owner decisions will be sampled over time. In essence, we proposed to study behavior enacted on the landscape, rather than individual people. Data derived from this network and sampling will inform land use scenario modeling efforts to forecast the future trajectory of the landscape, its rate of change, and subsequent potential provision of ecosystem services. The network was established to monitor change over time in the future, but an important aspect was to establish the baseline and antecedent circumstances that led to existing conditions. A classic historic study following specific decision-making over time on land ownership over generations is told in the Sanderson Farm story at the Harvard Forest: http://www.foresthistory.org/Publications/FHT/FHT1997/SandersonsFarm.pdf Establishment of the baseline and historic circumstances will inform models of future decisions. The summer 2009 project was a proof-of-concept to test the extent to which points could be established and an
Evidence Accumulation in Value-Based decisions
Open the record for dataset details and reuse information.
Social Decision-Making Risky Choice Task Dataset
Open the record for dataset details and reuse information.
Memory and decision making dataset
Open the record for dataset details and reuse information.
Automated Literature Screening for Systematic Reviews: Dataset for Evaluation Against Human Title and Abstract and Full-Text Screening Decisions
<p>This Zenodo entry contains the supplementary material associated with the manuscript titled <em>Automated Literature Screening for Systematic Reviews: A 5-Tier Prompting Approach Meeting Cochrane’s Sensitivity Requirement of Greater Than 0.99.</em> The paper will be presented at <a href="https://dbis.rwth-aachen.de/LLMs4MI2024/">LLMsMI 2024</a> in November 2024.</p> <p>A script is provided for replicating the executed experiments, along with a comprehensive evaluation file that reports all the experiment results. Provided data files represent an extension to the original datasets as provided by [1]. For associated systematic review manuscripts and eligibility criteria, please refer to [1] as well. </p> <p>[1] Guo, Eddie; Gupta, Mehul; Deng, Jiawen; Park, Ye-Jean; Paget, Mike; Naugler, Christopher (2023). "Automated Paper Screening for Clinical Reviews Using Large Language Models." <em>Mendeley Data</em>, V1, doi: 10.17632/np79tmhkh5.1. Accessed from: <a href="https://data.mendeley.com/datasets/np79tmhkh5/1" target="_new" rel="noopener">https://data.mendeley.com/datasets/np79tmhkh5/1</a>.</p>
A living catalogue of artificial intelligence datasets and benchmarks for medical decision making
<p>We provide a comprehensive curated catalogue of <strong>artificial intelligence datasets</strong> and <strong>benchmarks for medical decision making</strong>. At the time of first release (April 2021), the dataset contains more than 400 biomedical and clinical datasets of which 252 are publicly available or available upon request.</p> <p>The dataset was compiled based on a systematic literature review covering both biomedical and computer science literature and grey literature data sources. All datasets were manually systematized and annotated for meta-information, such as:</p> <ul> <li>Availability and licensing information</li> <li>Type of source data</li> <li>Links to source publications, main references or dataset repositories</li> </ul> <p>Benchmark dataset were additionally annotated for the following information:</p> <ul> <li>Associated task</li> <li>Performance metrics commonly used for evaluation</li> <li>Clinical relevance</li> <li>The availability of data splits</li> </ul> <p>In addition to the versioned TSV file on Zenodo, the dataset can also be explored live via <a href="https://docs.google.com/spreadsheets/d/1QjUxxnZ3tuyW5dj6nkt_o5yJcWUZec4ttfJxO8Zlty4/edit?usp=sharing">this Google Spreadsheet</a>. The dataset is intended as a living, extendable resource. Edit suggestions and additions are encouraged and can be submitted via the comment function of the Google sheet.</p> <p> </p> <p><strong>File descriptions</strong></p> <p><em>annotated-datasets.tsv</em> -- contains the annotated datasets</p> <p><em>arXiv-literature-export.tsv</em> -- contains the original literature record export from arXiv</p> <p><em>pubmed-literature-export.tsv</em> -- contains the original literature record export from PubMed</p> <p><em>README.md</em> -- contains a detailed description of all annotation fields</p>
A list of newly (re)appearing alien species in Belgium in support of decision making
<h2><strong>Context</strong></h2> <p>Invasive alien species are an important driver of biodiversity loss. Policy responses are developed to address this threat and need to be based on the best available data, including information from alien species registries and occurrence data. The Tracking Invasive Alien Species (<a href="http://trias-project.be" target="_blank" rel="noopener">TrIAS</a>) project implemented a workflow based on FAIR principles to identify new species in Belgium. These are species that have been newly observed on the territory or that were newly added to a species registry or checklist. The workflow is built on the Global Biodiversity Information Facility (GBIF) and uses the Belgian Global Register of Introduced and Invasive Species (<a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">GRIIS Belgium</a>) as a baseline for comparison. </p> <h2><strong>Description</strong></h2> <p>This dataset contains the outputs of the <a href="https://trias-project.github.io/indicators/06_occurrence_indicators_appearing_taxa.html" target="_blank" rel="noopener">pipeline</a> that generates a list of new alien species occurring in Belgium. This pipeline retrieves alien taxa from openly published species checklists or occurrence datasets on GBIF and compares this list with the <a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">Global Register of Introduced and Invasive Species - Belgium</a> (GRIIS Belgium) which is published by the IUCN Invasive Species Specialist Group (ISSG). This register is based on the <a href="https://github.com/trias-project/unified-checklist" target="_blank" rel="noopener">unified checklist of alien species in Belgium</a> which was created by TrIAS in support of research and policy using an open and reproducible workflow. Appearing/reappearing species are defined as follows:</p> <ul> <li>Appearing: an alien species which newly occurs on the Belgian territory in the three years before the year of the GBIF download used for creating the <a href="../records/10527772" target="_blank" rel="noopener">occurrence cube for non-native taxa in Belgium</a>. We will refer to this 3 years period as <em>evaluation period</em>.</li> <li>Re-appearing: an alien species reappearing on the Belgian territory after a latency of 4 years or more. For example, we consider a taxon reappearing in 2022 if observations occur in 2022 and 2018 or before.</li> </ul> <h2><strong>Files</strong></h2> <ul> <li><code>appearing_taxa.tsv</code></li> <li><code>reappearing_taxa.tsv</code></li> </ul> <h2><strong>Field values</strong></h2> <p>Field values of <code>appearing_taxa.csv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey</li> <li><code>canonicalName</code>: scientific species name</li> <li><code>year</code>: year of appearance</li> <li><code>ncells_prot_areas</code>: number of 1x1km grid cells in protected areas</li> <li><code>ncells_BE</code>: number of 1x1km grid cells in Belgium</li> <li><code>in_prot_areas</code>: species occurs for the first time in protected areas of NATURA2000 in Belgium during the evaluation period (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>in_BE</code>: species occurs for the first time in Belgium during the evaluation period(<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>class</code></li> <li><code>kingdom</code></li> <li><code>classKey</code></li> <li><code>kingdomKey</code></li> </ul> <p>Field values of <code>reappearing_taxa.csv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey</li> <li><code>canonicalName</code>: scientific species name</li> <li><code>year</code>: year of reappearance</li> <li><code>ncells_prot_areas</code>: number of 1x1km grid cells in protected areas</li> <li><code>ncells_BE</code>: number of 1x1km grid cells in Belgium</li> <li><code>in_prot_areas</code>: species reappears in protected areas of NATURA2000 in Belgium (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>in_BE</code>: species reappears in Belgium during the evaluation period (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>n_latent_years</code>: latency, in year, i.e. the number of years since last occurrence in Belgium</li> <li><code>class</code></li> <li><code>kingdom</code></li> <li><code>classKey</code></li> <li><code>kingdomKey</code></li> </ul> <h2><strong>Potential uses of the dataset</strong></h2> <p>The list of newly (re)appearing alien species in Belgium can be used for various purposes:</p> <ul> <li>to update the Belgian GRIIS checklist</li> <li>to flag the occurrence of new, regulated species on the territory (early warning)</li> <li>to develop a rapid response </li> <li>to select species for quick impact assessment</li> <li>to select species for risk assessment</li> <li>to draft alert lists</li> <li>for horizon scanning alien species</li> <li>to select species for risk assessment</li> <li>to identify new introduction patways</li> <li>...</li> </ul>
Bibliographic Data from the Digital Twin Anomaly Detection Decision-Making for Bridge Management Systematic Review
<p>This database contains all the bibliographic information about the 8673 records found after applying the Search Strategy used for the Digital Twin Anomaly Detection Decision-Making for Bridge Management Systematic Review. Such strategy consisted on using seven initial keywords and similar terms of interest (namely: bridge and bridges, etc.): </p> <ul> <li>Bridge.</li> <li>Digital twin.</li> <li>Bridge information modelling.</li> <li>Finite elements.</li> <li>Bridge health monitoring.</li> <li>Anomaly detection algorithm.</li> <li>Cultural heritage.</li> </ul> <p>Six initial queries were done combining the first keyword with the rest of them:</p> <ul> <li>bridge* AND "digital twin*"</li> <li>bridge* AND (BrIM OR "bridge information model*")</li> <li>bridge* AND (FEM OR FEA OR "finite element method*" OR "finite element analy*")</li> <li>bridge* AND ("bridge health monitoring" OR "structural health monitoring")</li> <li>bridge* AND (ADA OR "anomaly detection algorithm*")</li> <li>bridge* AND ("cultural heritage" OR "monument* bridge*" OR "old bridge*" OR "ancient bridge*" OR "historic* bridge*")</li> </ul> <p>As a first screening step, the combination of these 6 initial searches was done to obtain relevant works containing at least three of the main keywords of interest:</p> <ul> <li>#1 AND #2</li> <li>#1 AND #3</li> <li>#1 AND #4</li> <li>#1 AND #5</li> <li>#1 AND #6</li> <li>#2 AND #3</li> <li>#2 AND #4</li> <li>#2 AND #5</li> <li>#2 AND #6</li> <li>#3 AND #4</li> <li>#3 AND #5</li> <li>#3 AND #6</li> <li>#4 AND #5</li> <li>#4 AND #6</li> <li>#5 AND #6</li> </ul> <p>All records found in Scopus where downloaded both in .ris and .csv format and are included in this database. The search was conducted on 10/12/2022.</p> <p>Note: Searches 10, 14, 17 and 21 did not return any records.</p>
Contractual Events in Court Decisions Dataset
<p>A dataset for the task of information extraction, in particular event extraction, in court decisions, focusing on contracts. Our dataset captures contractual relations and events that affect them in some way, such as negotiations preceding a (possible) contract, the execution of a contract, or its termination.</p>
EJR01 Foraging decisions underlying restricted space-use: effects of fire and forage maturation on large herbivore nutrient uptake on Konza Prairie
Recent models suggest that herbivores optimize nutrient intake by selecting patches of low to intermediate vegetation biomass. We assessed the application of this hypothesis to plains bison (Bison bison) in an experimental grassland managed with fire by estimating daily rates of nutrient intake in relation to grass biomass and by measuring patch selection in experimental watersheds in which grass biomass was manipulated by prescribed burning. Digestible crude protein content of grass declined linearly with increasing biomass, and the mean digestible protein content relative to grass biomass was greater in burned watersheds than watersheds not burned that spring (intercept; F1,251 = 50.57, P < 0.0001). Linking these values to published functional response parameters, ad libitum protein intake, and protein expenditure parameters, Fryxell's (Am. Nat., 1991, 138, 478) model predicted that the daily rate of protein intake should be highest when bison feed in grasslands with 400 - 600 kg/ha. In burned grassland sites, where bison spend most of their time, availability of grass biomass ranged between 40 and 3650 kg/ha, bison selected foraging areas of roughly 690 kg/ha, close to the value for protein intake maximization predicted by the model. The seasonal net protein intake predicted for large grazers in this study suggest feeding in burned grassland can be more beneficial for nutrient uptake relative to unburned grassland as long as grass regrowth is possible. Foraging site selection for grass patches of low to intermediate biomass help explain patterns of uniform space use reported previously for large grazers in fire-prone systems. This data set was used to test the forage maturation hypothesis in the Konza Prairie bison enclosure from 2012-2013. Our objectives were to quantify foraging site selection of Plains bison in order to determine if bison in a fire-prone grassland selected sites of low-to-intermediate forage biomass as posited by Fryxell’s (1991) forage mat
Perceptual decisions result from the continuous accumulation of memory and sensory evidence
Open the record for dataset details and reuse information.
Simultaneous EEG-fMRI - Confidence in perceptual decisions
Open the record for dataset details and reuse information.
Inference based decisions in a hidden state foraging task: differential contributions of prefrontal cortical areas
<p>Tabular dataset of behavioral data in the hidden state foraging task. The data is stored as a unique table, with one row per "attempt", i.e. a poke for mice and a tap for humans.</p> <p>The table includes four distinct experiments, encoded in the Experiment column. Experiment "Learning" refers to Fig. 2, experiment "VaryingParameters" refers to Fig. 2h and Fig.3. Experiment "LearningAndVaryingParameters" refers to Fig. 4. Experiment "OptogeneticInactivation" refers to Fig. 5.</p> <p>The column "TestingSession" defines whether those sessions were used for the analysis. It is used to exclude adaptation sessions to a new protocol for rodents in the "VaryingParameters" and "OptogeneticInactivation" experiments.</p> <p>In the human case, after an incorrect transition the subject receives an error cue and does not tap. This is considered a "trial" (and also a "streak") but not an attempt. This causes the StreakNumber and PokeNumber columns to increase by 2 after an error cue.</p>
Artificial Intelligence for EU Decision-Making: Effects on Citizens Perceptions of Input, Throughput and Output Legitimacy
<p>The uploaded dataset was used for the statistical analysis of the pre-print "Artificial Intelligence for EU Decision-Making: Effects on Citizens’ Perceptions of Input, Throughput and Output Legitimacy" (Permanent identifier: <a href="https://arxiv.org/abs/2003.11320">arXiv:2003.11320</a>)</p> <p>A lack of political legitimacy undermines the ability of the European Union (EU) to resolve major crises and threatens the stability of the system as a whole. By integrating digital data into political processes, the EU seeks to base decision-making increasingly on sound empirical evidence. In particular, artificial intelligence (AI) systems have the potential to increase political legitimacy by identifying pressing societal issues, forecasting potential policy outcomes, informing the policy process, and evaluating policy effectiveness. This paper investigates how citizens’ perceptions of EU input, throughput, and output legitimacy are influenced by three distinct decision-making arrangements: (1) independent human decision-making (HDM); (2) independent algorithmic decision-making (ADM) by AI-based systems; and (3) hybrid decision-making by EU politicians and AI-based systems together. The results of a pre-registered online experiment (n = 572) suggest that existing EU decision-making arrangements are still perceived as the most democratic (input legitimacy). However, regarding the decision-making process itself (throughput legitimacy) and its policy outcomes (output legitimacy), no difference was observed between the status quo and hybrid decision-making involving both ADM and democratically elected EU institutions. Where ADM systems are the sole decision-maker, respondents tend to perceive these as illegitimate. The paper discusses the implications of these findings for (a) EU legitimacy and (b) data-driven policy-making.</p>
Dynamic meta-analysis: a method of using global evidence for local decision making (supplementary materials)
<p>Dynamic meta-analysis: a method of using global evidence for local decision making (supplementary materials)</p>
Evaluating demand forecasting models using multi-criteria decision-making approach
<p>The datasets added include the raw data, ANP weights calculations and TOPSIS ranking calculations for the demonstration case in the article titled: Evaluating demand forecasting models using multi-criteria decision-making approach.</p> <p>The files include a data explanation text file.</p>
Image Repository Decision Tree - Where do I deposit my imaging data
<p>Depositing data in quality data repositories is one crucial step towards FAIR (Findable, Accessible, Interoperable, and Reusable) data. Accordingly, Euro-BioImaging strongly encourages sharing scientific imaging data in established, thematic repositories. </p> <p>To guide you in the selection of appropriate repositories, we have created an overview of available repositories for different types of image data, including their scope and requirements. This decision tree guides you through questions about your data and directs you to the correct repository, and/or provides instructions for further processing to meet the critera of the repositories. </p> <p>Three seperate trees are provided for different classes of imaging data: open bioimage data, preclinical data, and human imaging data. These versions with three trees can be used for web-view. Update: also the editable versions in powerpoint format (.pptx) are now provided. Please be aware that opening the versions with another program might lead to shifted formatting.</p> <p>Update: we now also provide ready-to-print versions designed to be printed on A3 format. One page shows the open bioimaging data tree and one page combines the preclinical and human imaging data trees. Also the editable versions of these are provided.</p>
General CCU (Product) Acceptance & Trade-Off Decisions
<p>The dataset obtained for WP6 of the CO2SMOS project contains anonymized data including demographic and attitudinal information, perceptions of benefits and barriers regarding CCU adoption and acceptance data obtained from a choice-based conjoint experiment on trade-off decisions in CCU product purchase situations, obtained through an online survey conducted with participants from Germany, Norway, Poland, and Spain.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.