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We present the results of Galaxy Nurseries project, which was designed toenable crowdsourced analysis of slitless spectroscopic data by volunteercitizen scientists using the Zooniverse online interface. The dataset wasobtained by the WFC3 Infrared Spectroscopic Parallel (WISP) Surveycollaboration and comprises NIR grism (G102 and G141) and direct imaging.Volunteers were instructed to evaluate indicated spectral features and decidewhether it was a genuine emission line or more likely an artifact. GalaxyNurseries was completed in only 40 days, gathering 414,360 classifications from3003 volunteers for 27,333 putative emission lines. The results of GalaxyNurseries demonstrate the feasibility of identifying genuine emission lines inslitless spectra by citizen scientists. Volunteer responses for each subjectwere aggregated to compute $f_{\mathrm{Real}}$, the fraction of volunteers whoclassified the corresponding emission line as "Real". To evaluate the accuracyof volunteer classifications, their aggregated responses were compared withindependent assessments provided by members of the WISP Survey Science Team(WSST). Overall, there is a broad agreement between the WSST and volunteers'classifications, although we recognize that robust scientific analysestypically require samples with higher purity and completeness than rawvolunteer classifications provide. Nonetheless, choosing optimal thresholdvalues for $f_{\mathrm{Real}}$ allows a large fraction of spurious lines to bevetoed, substantially reducing the timescale for subsequent professionalanalysis of the remaining potential lines.

Galaxy Nurseries: Crowdsourced analysis of slitless spectroscopic data