{"title": "LabPredict", "logoImg": "bafkreicfqkrqkmevmtjeth52xwr6ykvs4ppeypkdfkskd6kkrostj5vu6u", "website": "https://labpredict.xyz", "bannerImg": "bafkreicltnxbhtipu6mpzrtuulnssjrjpuorxd65x2uozsm76zkw7sgjre", "createdAt": 1682366420471, "credentials": {"twitter": {"type": ["VerifiableCredential"], "proof": {"jws": "eyJhbGciOiJFZERTQSIsImNyaXQiOlsiYjY0Il0sImI2NCI6ZmFsc2V9..1okf4K_GlAQA8Z78rq298yJJzzYOzgKNM-h903STB5It-MBKcMtId-9NTojsFc-sXp6JKfVZlq7ssLZjKgB1DQ", "type": "Ed25519Signature2018", "created": "2023-04-24T19:53:46.729Z", "proofPurpose": "assertionMethod", "verificationMethod": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC#z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC"}, "issuer": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC", "@context": ["https://www.w3.org/2018/credentials/v1"], "issuanceDate": "2023-04-24T19:53:46.729Z", "expirationDate": "2023-07-23T19:53:46.729Z", "credentialSubject": {"id": "did:pkh:eip155:1:0x1d1Caa3A187AfBdF298a32a79DfC34F3BB22952F", "hash": "v0.0.0:/cpxWtxRVJtFU9T/1DFHom896zpcFudR/TDqzsKdv2k=", "@context": [{"hash": "https://schema.org/Text", "provider": "https://schema.org/Text"}], "provider": "ClearTextTwitter#LabPredict_"}}}, "description": "# Project Description\nLabPredict is a prediction market designed to make longevity research interesting, accessible, and collaborative for a diverse audience. Our primary goal is to foster engagement and harness the collective wisdom of researchers, data scientists, and enthusiasts to predict the outcomes of aging research experiments. By bringing together a community passionate about scientific discovery, LabPredict aims to accelerate the identification of effective interventions that can promote an extended lifespan.\nThe platform will focus on surrogate model organisms, such as yeast, nematodes, and fruit flies, which have relatively short lifespans and provide quicker results. This approach will enable participants to engage with the platform more frequently and contribute to the scientific understanding of aging-related processes.\n\n# Example\nDr. Smith, a researcher at a leading university, has published a paper about a novel drug that targets a specific cellular pathway associated with aging. Dr. Smith believes that the drug has the potential to extend the healthspan of fruit flies. An enthusiastic member of the LabPredict community discovers Dr. Smith's paper and sets up a prediction market with the following question:\n\"Will the novel drug X extend the healthspan of fruit flies by at least 20% when compared to the control group in a third-party CRO validated experiment?\"\nLabPredict users, including researchers, data scientists, and aging enthusiasts, start evaluating the information provided by the paper. Based on their analysis, they make predictions on the outcome of a third-party CRO (Contract Research Organization) validated experiment involving Dr. Smith's drug.\nOnce the CRO conducts the experiment, the outcomes are shared with the LabPredict community. The platform then evaluates the predictions made by the users and rewards those who accurately predicted the outcome. The type of reward is still to be determined.  This process not only incentivizes users to participate and contribute their knowledge but also helps identify the most knowledgeable and skilled predictors in the community.\nBy using LabPredict, the community has collaboratively assessed the potential of the novel drug in a transparent, data-driven manner. This process accelerates the evaluation of new interventions, fosters scientific collaboration, and contributes to the broader understanding of aging and healthspan.\n\n# Key Features\n1. Dynamic Market Structure: LabPredict will feature a well-organized, user-friendly market structure focused on specific questions related to longevity research, enabling users to easily navigate through various propositions, filter them by organism type or research area, and track the performance of their predictions over time.\n\n2. Information Aggregation and Incentives: LabPredict will facilitate the aggregation of diverse information and opinions, including scientific research, technological advancements, and potential breakthroughs in aging and lifespan extension. By offering financial incentives for accurate predictions, the platform will encourage participants to research and analyze relevant data, contributing to an improved understanding of factors affecting model organism longevity.\n\n3. Blockchain Integration and Market Data: Leveraging blockchain technology, LabPredict will ensure transparency, security, and decentralization of the prediction market, enabling trustless and tamper-proof trading of contracts. Contract prices and trading volumes will provide valuable insights into the consensus views on the future of model organism longevity, informing decision-making by researchers, policymakers, and other stakeholders.\n\n# Benefits\n1. Accelerated Evaluation of Interventions: By leveraging the collective wisdom of the LabPredict community, the platform enables a more rapid assessment of the potential effects of novel aging interventions. This accelerated evaluation can help prioritize research efforts and allocate resources more efficiently.\n\n2. Falsifiable and Clear Research Claims: LabPredict encourages researchers to formulate precise and testable hypotheses that can be validated through experiments. This approach promotes clear and falsifiable claims, which are essential for scientific progress and reduce the likelihood of ambiguous or misleading results.\n\n3. Incentivizing Reproducible Research: As LabPredict rewards accurate predictions and contributions, the platform inherently incentivizes reproducible research. Users are encouraged to share detailed methodologies and data, which facilitates transparency and allows others to verify the findings independently.\n\n4. Community-Driven Innovation: LabPredict fosters a collaborative environment where researchers, data scientists, and enthusiasts can exchange ideas, insights, and expertise. This community-driven approach can lead to innovative hypotheses and experimental designs that might not emerge from individual efforts, ultimately contributing to the advancement of aging research.\n\n# Considerations\n1. Compliance: The platform will operate within the bounds of applicable laws and regulations. We are consulting with legal experts to navigate potential concerns related to prediction markets, incentives (if any), and jurisdictions.\n\n2. Ethics: There are ethical concerns arising from the trading of contracts based on the lifespan of living organisms. We will address these concerns by forming an institutional review board, promoting responsible research, and adhering to high animal welfare standards.\n\n# Funding Request\nWe are seeking funding through the Gitcoin round to support the development and launch of LabPredict. The funds will be allocated as follows:\n\n1. Development: Building the prediction market platform, integrating blockchain-based infrastructure, and creating user-friendly interface.  \n\n2. Initial CRO Contracting: Covering the costs of contracting with a third-party Contract Research Organization (CRO) to validate the initial set of experiments. As LabPredict becomes self-sustaining, the platform will generate revenue through trading fees to cover future CRO contracts and ongoing operational costs.\n\n# Conclusion\nLabPredict has the potential to change the way the public interacts with aging research and make science more engaging and collaborative. The main goal is not only to accelerate scientific discovery but also to ignite excitement and enthusiasm for science among a wider audience. By breaking down the barriers of the traditional \"ivory tower\" and encouraging collaboration and openness, LabPredict aims to democratize scientific inquiry and inspire more people to contribute their unique perspectives and expertise. With your support, we can build a platform that celebrates scientific engagement, promotes transparency, and drives community-driven innovation in the field of aging research.", "logoImgData": {}, "bannerImgData": {}, "projectTwitter": "LabPredict_"}