{"id":"W3118308033","doi":"10.2139/ssrn.3039037","title":"Storm Crowds: Evidence from Zooniverse on Crowd Contribution Design","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Open Source Software Innovations","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Crowds; Storm; Computer science; Computer security; Geography; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008851759,0.000492834,0.0004901853,0.002390944,0.003537695,0.003585391,0.00130682,0.002552342,0.02292779],"category_scores_gemma":[0.07273614,0.0004752029,0.0002856075,0.002201593,0.003040171,0.004991123,0.004707441,0.001179459,0.00383602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174842,"about_ca_system_score_gemma":0.001586149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008799165,"about_ca_topic_score_gemma":0.009869855,"domain_scores_codex":[0.9931535,0.003834054,0.0001838138,0.0007510128,0.001634623,0.0004429586],"domain_scores_gemma":[0.9043872,0.06682828,0.009354297,0.01090798,0.00551322,0.003009052],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.005636828,0.001444236,0.2806657,0.001691432,0.0006747116,0.001762807,0.1058844,0.0122382,0.005457224,0.1291548,0.1107128,0.3446769],"study_design_scores_gemma":[0.001131001,0.001085702,0.3224807,0.001312118,0.0003697533,0.001276808,0.07410663,0.03385208,0.006205029,0.2287479,0.3290551,0.0003771058],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7566463,0.001401771,0.0168786,0.004592058,0.0002820659,0.0003445778,0.001461793,0.0004681376,0.2179247],"genre_scores_gemma":[0.9854648,0.0003101761,0.00311263,0.000482629,0.00009958682,0.0001312827,0.0005182552,0.0001418812,0.009738837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9911482,"threshold_uncertainty_score":0.0767011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03305044846674252,"score_gpt":0.2848114759182334,"score_spread":0.2517610274514909,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}