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1,663 results for “BIAS”
Plasma induced signatures reveal an extracellular milieu possessing an immunoregulatory bias in treatment naïve inflammatory bowel disease
GEO Series GSE71730. Homo sapiens. 47 samples. Type: Expression profiling by array.
Foxp3-specific deletion of CREB generates Th2 biased ST-2 positive regulatory T-cells with enhanced IL-10 production and suppressive capacity
GEO Series GSE157693. Mus musculus. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Abstractive Snippet Generation (query-biased DMOZ descriptions)
<p>Abstractive Snippet Generation (query-biased DMOZ descriptions).</p>
Data from: A problem of bias and response heterogeneity, in Standing With Giants: A Collection of Public Health Essays in Memoriam to Dr. Elizabeth M. Whelan
There is extensive literature on the question, "Does air quality have health effects?" For example, Google Scholar gives 199,000 hits for ("mortality" and "air pollution"). See Health Effects Institute (2010) and editorial by Brauer and Mancini (2014), for example. One paper that appeared in 1993 has over 6,000 citations. The vast majority of these papers find a positive association between air quality health effects (death). A few papers make the case that if potential bias is carefully taken into account then there is no association between air quality and deaths, e.g. Chay et al. (2003), Enstrom (2005), Janes et al. (2007), Greven et al. (2011), Cox et al. (2013). Clearly the weight of evidence is for a positive association, but for any particular type of claim, logically it takes only one true negative to negate all the positives associations with respect to causation for that claim. A real, causative claim should always be detected in a well-designed and properly run experiment. What are some of the factors that lead to these discordant literature results?
Dataset to Analyze Propaganda in Tweets From Politically Biased Sources
<p><span>Our dataset consists of 32,047 tweets from 44 ac</span><span>count associated with 11 news outlets downloaded between</span><br><span>27th</span><span> </span><span>September 2022 to 3rd</span><span> </span><span>October 2022, from Twitter using </span><span>Twitter Streaming API.</span><br><span>Each tweet is a record that contains the tweet id, number </span><span>of likes, retweet count, isretweeted status, associated bias of</span><br><span>the new outlets according to AllSides Media Bias rating</span><span>, </span><span>and model prediction(1 for propaganda and 0 for non-propaganda)</span></p>
Data from: Revealing biases in insect observations a comparative analysis between academic and citizen science data
<p>Data and code used in the article "Revealing biases in insect observations a comparative analysis between academic and Citizen Science data".</p>
Simulation Data for Comparison of Bias Reduction Methods for Logistic Regression
<p>Simulation Results for "Comparison of Bias Reduction Methods for Logistic Regression</p> <p>Resultsp.RData include the raw simulation results for p = 1, 4, 8</p> <p>Statsp.RData include the summarized simulation results for p = 1, 4, 8</p>
Rewritten Media Bias News Headlines
<p>This dataset was used in the paper "Rewriting Bias: Mitigating Media Bias in News Recommender Systems through Automated Rewriting" by Qin Ruan, Jin Xu, Susan Leavy, Brian Mac Namee, and Ruihai Dong, presented at the 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP'24), July 1-4, 2024, in Cagliari, Italy. (ACM, New York, NY, USA, 10.1145/3627043.3659541).</p> <p>The dataset includes seven distinct rewritten versions of news headlines generated using the following methods proposed in the paper: RADJ, RADV, RNOUN, RVERN, RALL, RG3.5, and RG4.0.</p> <p>The rewriting approaches are categorised into two main categories: <strong>Word Replacement </strong>approaches and <strong>Large Language Models </strong>approaches.</p> <p>1.Sentence Rewriting Using Word Replacement :</p> <ul> <li><strong>Replace Adjectives (RADJ)</strong>: This approach replaces adjectives identified as contributing to bias with neutral or opposite ones.</li> <li><strong>Replace Adverbs (RADV)</strong>: This approach replaces adverbs identified as contributing to bias with neutral or opposite ones.</li> <li><strong>Replace Nouns (RNOUN)</strong>: This approach replaces nouns identified as contributing to bias with neutral or more general ones.</li> <li><strong>Replace Verbs (RVERB)</strong>: This approach replaces verbs identified as contributing to bias with neutral or more factual ones.</li> <li><strong>Replace All (RALL)</strong>: This is a combination of all the above approaches.</li> </ul> <p>2.Sentence Rewriting Using Large language Models:</p> <ul> <li><strong>Sentence Rewriting using GPT-3.5 (RG3.5)</strong>: This method rephrases sentences using GPT-3.5 based on a specific prompt.</li> <li><strong>Sentence Rewriting using GPT-4.0 (RG4.0)</strong>: This method rephrases sentences using GPT-4.0 based on a specific prompt.</li> </ul> <p>The dataset consists of original news headlines and their corrsponding rewritten versions prodcued by each of the seven approaches mentioned above. Each rewritten version aims to reduce bias while maintaining the original meaning.</p> <p> </p> <p><strong>Dataset Structure:</strong></p> <p>The dataset consists of a single file with the following columns:</p> <ul> <li>NewsId: A unique identifier for each news article.</li> <li>Original: The original headline of the news article.</li> <li>RG3.5: The headline rewritten using the <a href="https://platform.openai.com/docs/models/gpt-3-5">GPT-3.5</a> model.</li> <li>RG4.0: The headline rewritten using the <a href="https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo">GPT-4.0</a> model.</li> <li>RADJ: The headline with adjectives replaced to reduce bias.</li> <li>RADV: The headline with adverbs replaced to reduce bias.</li> <li>RVERB: The headline with verbs replaced to reduce bias.</li> <li>RNOUN: The headline with nouns replaced to reduce bias.</li> <li>RALL: The headline with adjectives, adverbs, verbs. noun replaced to reduce bias.</li> </ul> <p><strong>Usage:</strong></p> <p>This dataset can be used to study the impact of different sentence rewriting approaches on reudicng bias in enws healines. It is also suitable for researchers interested in natural language processing, media bias reduction, and the application of large language models in generative AI.</p> <p>For more information, please visit <a href="https://github.com/ruanqin0706/MediaBiasinNewsRec">https://github.com/ruanqin0706/MediaBiasinNewsRec</a></p> <p><strong>Contact Information: </strong>qin.ruan@ucdconnect.ie</p>
Seasonal biases in fluorescence estimated chlorophyll-a derived from biogeochemical profiling floats
Open the record for dataset details and reuse information.
Fig. 1 in A dragonfly in the desert: genetic pathways of the widespread Trithemis arteriosa (Odonata: Libellulidae) suggest male-biased dispersal
Fig. 1 Sampling localities in Namibia and Kenya (left) with a detailed map of Namibia (right) illustrating the ephemeral river catchments and the geological relief. N Numbers of individuals for each population.
Bias correction for convective mass flux
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FIGURE 1 in New records of riverweeds (Podostemaceae) from the tropical Andes (Ecuador and Colombia): getting our feet wet to bypass collection bias in Neotropical rivers
FIGURE 1. Podostemaceae recorded in fast-flowing aquatic ecosystems in Andean rivers of Ecuador and Colombia. a) Lophogyne cf. aeruginosa collected in Saloya River in Ecuador. The habit, prostrate stem, flowers each subtended by a spathella, stamens (two) on one side of ovary, lack of andropodium, and capsular fruits are shown. b) Tristicha trifaria collected in Ancho River in Colombia (top), Arenal River in Colombia (bottom left), and in Caoni River, Ecuador (bottom center and bottom right). The habit, tristichous leaves (photosynthetic shootlets or ramuli), stigmas (three), bracts (two) enclosing the flower before anthesis, the single stamen in a flower, and capsular fruits are shown. Information on the specific localities is in Table 1.
Figure 4 in Male-biased in-water population of loggerhead turtle (Caretta caretta) in Dalyan, Turkey possible important marine turtle area in the Mediterranean
Figure 4. Comparison of body mass between female, male and subadult individuals (The line in the boxes represents the median value, the boxes represent interquartile range between first and third quartiles).
Figure 3 in Male-biased in-water population of loggerhead turtle (Caretta caretta) in Dalyan, Turkey possible important marine turtle area in the Mediterranean
Figure 3. Comparison of SCL and CCL between female, male and subadult individuals (The line in the boxes represents the median value, the boxes represent interquartile range between first and third quartiles).
Sex-biased architecture guides T cell development through spatially defined niches - CODEX images
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Brief, Remote Treatment of Youth Injection Phobia and Measurement of Novel, Disorder-congruent Cognitive Bias Tasks
ClinicalTrials.gov study NCT04972006. IPD Sharing: NO. Countries: 0. Publications: 0.
Emotional Attention Bias Modification and Targeted Memory Reactivation in Alcohol Use Disorder
ClinicalTrials.gov study NCT06457113. IPD Sharing: NO. Countries: 0. Publications: 0.
Clinical Study of G Protein Biased Μ - Opioid Receptor Agonist Oliceridine for Optimizing Postoperative Analgesia Under General Anesthesia
ClinicalTrials.gov study NCT06668298. IPD Sharing: NO. Countries: 0. Publications: 0.
Outcome, Hindsight and Implicit Bias in Emergency Medicine and Medical Disciplinary Law.
ClinicalTrials.gov study NCT05424497. IPD Sharing: NO. Countries: 0. Publications: 0.
Beyond Race: Objectively Assessed Skin Color and Its Association With Pulse Oximeter Bias in Critically Ill Infants
ClinicalTrials.gov study NCT05994417. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
ScienceDex guides
Understand access before you commit
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.