{"id":"W2961436936","doi":"10.21083/partnership.v14i1.4632","title":"Crowding the library: How and why libraries are using crowdsourcing to engage the public","year":2019,"lang":"en","type":"article","venue":"Partnership The Canadian Journal of Library and Information Practice and Research","topic":"Open Source Software Innovations","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; University of Alberta","funders":"","keywords":"Crowdsourcing; Outreach; Mandate; Citizen journalism; Public relations; World Wide Web; Best practice; Creativity; Perspective (graphical); Sociology; Data science; Computer science; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02306022,0.000899075,0.0009223924,0.005990622,0.03725463,0.04331842,0.004326253,0.008182282,0.01115038],"category_scores_gemma":[0.04838103,0.000914784,0.001085207,0.009552657,0.03656198,0.03015484,0.0179963,0.006205446,0.005119776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03206393,"about_ca_system_score_gemma":0.04152981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1809955,"about_ca_topic_score_gemma":0.2043682,"domain_scores_codex":[0.9593073,0.01901605,0.001107416,0.003038753,0.01320856,0.004321793],"domain_scores_gemma":[0.9487006,0.02737547,0.003044342,0.003475685,0.01310924,0.004294572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001622786,0.0001536154,0.01228534,0.003449248,0.0001184634,0.00151357,0.4243925,0.0009690091,0.002123525,0.1624991,0.1564049,0.2359284],"study_design_scores_gemma":[0.00002654647,0.00005818085,0.004649538,0.002197976,0.00005254533,0.0004809236,0.2758802,0.0007254593,0.001233024,0.04745342,0.6670119,0.0002303113],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1177158,0.03595255,0.04163237,0.4016717,0.003238343,0.000780627,0.0004093075,0.002211126,0.3963881],"genre_scores_gemma":[0.8334494,0.02018312,0.01652998,0.05160251,0.00114755,0.0005703875,0.0002533917,0.001065124,0.07519851],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9566815,"threshold_uncertainty_score":0.359884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0812155718093368,"score_gpt":0.3092977762504342,"score_spread":0.2280822044410974,"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."}}