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Crowdsourcing Without a Crowd
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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s10336-007-0239-9openalex-snapshot
Citizens, science and bird conservation
inferredcites →https://doi.org/10.1007/s10531-005-8375-0openalex-snapshot
Monitoring Matters: Examining the Potential of Locally-based Approaches
inferredcites →https://doi.org/10.1007/s10618-013-0306-1openalex-snapshot
Repeated labeling using multiple noisy labelers
inferredcites →https://doi.org/10.1007/s13280-015-0709-xopenalex-snapshot
Mapping species distributions: A comparison of skilled naturalist and lay citizen science recording
inferredcites →https://doi.org/10.1016/0378-3758(94)00121-bopenalex-snapshot
Smoothing categorical data
inferredcites →https://doi.org/10.1016/j.tree.2011.11.006openalex-snapshot
Data-intensive science applied to broad-scale citizen science
inferredcites →https://doi.org/10.1111/j.1365-2699.2012.02734.xopenalex-snapshot
Using biological traits to explain ladybird distribution patterns
inferredcites →https://doi.org/10.1111/j.1365-2966.2008.13689.xopenalex-snapshot
Galaxy Zoo: morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey ★
inferredcites →https://doi.org/10.1111/j.1472-4642.2012.00883.xopenalex-snapshot
Invasive alien predator causes rapid declines of native European ladybirds
inferredcites →https://doi.org/10.1145/1390156openalex-snapshot
Proceedings of the 25th international conference on Machine learning - ICML '08
inferredcites →https://doi.org/10.1145/1401890.1401965openalex-snapshot
Get another label? improving data quality and data mining using multiple, noisy labelers
inferredcites →https://doi.org/10.1145/1656274.1656278openalex-snapshot
The WEKA data mining software
inferredcites →https://doi.org/10.1145/2566486.2567989openalex-snapshot
Community-based bayesian aggregation models for crowdsourcing
inferredcites →https://doi.org/10.1145/2660114.2660123openalex-snapshot
Getting by with a Little Help from the Crowd
inferredcites →https://doi.org/10.1287/opre.2013.1235openalex-snapshot
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems
inferredcites →https://doi.org/10.1609/hcomp.v1i1.13076openalex-snapshot
Why Stop Now? Predicting Worker Engagement in Online Crowdsourcing
inferredcites →https://doi.org/10.1609/hcomp.v1i1.13088openalex-snapshot
SQUARE: A Benchmark for Research on Computing Crowd Consensus
inferredcites →https://doi.org/10.18653/v1/2021.emnlp-mainopenalex-snapshot
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
inferredcites →https://doi.org/10.1890/110273openalex-snapshot
Data validation in citizen science: a case study from Project FeederWatch
inferredcites →https://doi.org/10.2307/2346806openalex-snapshot
Maximum Likelihood Estimation of Observer Error-Rates Using the EM Algorithm
inferredcites →https://doi.org/10.3115/1220355openalex-snapshot
Proceedings of the 20th international conference on Computational Linguistics - COLING '04
inferredcites →https://doi.org/10.3115/1613715.1613751openalex-snapshot
Cheap and fast---but is it good?
inferredcites →https://doi.org/10.3897/zookeys.480.8803openalex-snapshot
Crowdsourcing the identification of organisms: A case-study of iSpot
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/rse2.84openalex-snapshot
Economical crowdsourcing for camera trap image classification
inferred← citeshttps://doi.org/10.1002/widm.1288openalex-snapshot
Machine learning from crowds: A systematic review of its applications
inferred← citeshttps://doi.org/10.1007/978-3-031-76742-5_9openalex-snapshot
Citizen Science: Theory and Applications
inferred← citeshttps://doi.org/10.1007/s13280-015-0705-1openalex-snapshot
Digital technology and the conservation of nature
inferred← citeshttps://doi.org/10.1007/s13280-015-0710-4openalex-snapshot
Taking a ‘Big Data’ approach to data quality in a citizen science project
inferred← citeshttps://doi.org/10.1016/j.ecoinf.2019.101010openalex-snapshot
Can we estimate insect identification ease degrees from their identification key paths?
inferred← citeshttps://doi.org/10.1016/j.ecoinf.2021.101313openalex-snapshot
Citizen science decisions: A Bayesian approach optimises effort
inferred← citeshttps://doi.org/10.1016/j.geoforum.2016.07.002openalex-snapshot
Imagining wildlife: New technologies and animal censuses, maps and museums
inferred← citeshttps://doi.org/10.1063/1.5055457openalex-snapshot
Assessing workers reliability in crowd-sourced computing using Bayesian rules
inferred← citeshttps://doi.org/10.1109/jiot.2017.2722358openalex-snapshot
A Machine Learning Decision-Support System Improves the Internet of Things’ Smart Meter Operations
inferred← citeshttps://doi.org/10.1109/tsc.2017.2674662openalex-snapshot
Crowdsourcing, Mixed Elastic Systems and Human-Enhanced Computing–A Survey
inferred← citeshttps://doi.org/10.1111/cobi.12705openalex-snapshot
The role of automated feedback in training and retaining biological recorders for citizen science
inferred← citeshttps://doi.org/10.1111/puar.12808openalex-snapshot
Crowdsourcing Government: Lessons from Multiple Disciplines
inferred← citeshttps://doi.org/10.1145/2851581.2890382openalex-snapshot
Species Identification in Citizen Science
inferred← citeshttps://doi.org/10.1145/3127325.3128330openalex-snapshot
Bumblebee friendly planting recommendations with citizen science data
inferred← citeshttps://doi.org/10.1145/3494522openalex-snapshot
A Survey on Task Assignment in Crowdsourcing
inferred← citeshttps://doi.org/10.1145/3555535openalex-snapshot
Consensus Building in On-Line Citizen Science
inferred← citeshttps://doi.org/10.1371/journal.pone.0218614openalex-snapshot
Evaluating the ability of citizen scientists to identify bumblebee (Bombus) species
inferred← citeshttps://doi.org/10.1371/journal.pone.0267114openalex-snapshot
How many people need to classify the same image? A method for optimizing volunteer contributions in binary geographical classifications
inferred← citeshttps://doi.org/10.22323/2.18010207openalex-snapshot
From citizen science to citizen action: analysing the potential for a digital platform to cultivate attachments to nature
inferred← citeshttps://doi.org/10.5334/cstp.567openalex-snapshot
X-Polli:Nation: Contributing Towards Sustainable Development Goals Through School-Based Pollinator Citizen Science
inferred← citeshttps://doi.org/10.5334/cstp.735openalex-snapshot
Image Recognition as a “Dialogic AI Partner” Within Biodiversity Citizen Science—an empirical investigation
inferred← citeshttps://doi.org/10.7287/peerj.5965v0.1/reviews/1openalex-snapshot
Peer Review #1 of "Designing online species identification tools for biological recording: the impact on data quality and citizen science learning (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj.5965v0.1/reviews/2openalex-snapshot
Peer Review #2 of "Designing online species identification tools for biological recording: the impact on data quality and citizen science learning (v0.1)"
inferred← citeshttps://doi.org/10.7717/peerj.5965openalex-snapshot
Designing online species identification tools for biological recording: the impact on data quality and citizen science learning
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