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Machine learning augmentation reduces prediction error in collective forecasting: development and validation across prediction markets with application to COVID events

eBioMedicine(2023)10.1016/j.ebiom.2023.104783Source: DataRank Database

Machine learning augmentation reduces prediction error in collective forecasting: development and validation across prediction markets with application to COVID events is a research paper published in eBioMedicine (2023). On theSindex it has a DataRank of 0.104. It has been cited 1 time.

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0.104DataRank · unranked

Scored on demand from live citation data

Open Access1 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)Impact (FWCI 0.22)OA: goldTopics (34)IDs (PubMed, PMC, OpenAlex)Annotations (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.104

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

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Authors (8)

Karl R Mattingly ORCID,Ellen Morwitch ORCID,Frederik Bossaerts ORCID,Manning Clifford,Chad Nash

Live enrichment

PubMed:37708701 PMC:PMC10502359 OpenAlex:https://openalex.org/W4386692350

National Health and Medical Research Council

Grant: GNT 1110200

National Health and Medical Research Council

Grant: GNT 1197234

Department of Industry, Science and Resources

Grant: IR 2101990

FWCI

0.22

Citation Percentile

0.7%

Citation Trend

2024

goldLicense: cc-by-nc-nd

journalhttp://www.thelancet.com/article/S2352396423003493/pdf

publisherhttp://www.thelancet.com/article/S2352396423003493/pdf

publisherhttps://api.elsevier.com/content/article/PII:S2352396423003493?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2352396423003493?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.ebiom.2023.104783

Fields of Study

Mobile Crowdsensing and CrowdsourcingSports Analytics and PerformanceForecasting Techniques and ApplicationsHumansPandemicsCOVID-19ForecastingAustraliaMachine Learning

MeSH Terms

Machine LearningCOVID-19AustraliaForecastingHumansPandemics

Keywords

Brier scoreMachine learningArtificial intelligenceLeverage (statistics)Prediction marketComputer scienceWeightingEconometricsCoronavirus disease 2019 (COVID-19)Event (particle physics)Predictive modellingSupport vector machineData miningEconomicsMedicineForecast AccuracyCollective IntelligenceCovidHuman-machine Forecast