{"id":"W6976792841","doi":"10.6084/m9.figshare.20063114","title":"Centaur VGI: An Evaluation of Engagement, Speed, and Quality in Hybrid Humanitarian Mapping","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"","keywords":"Volunteered geographic information; Usability; Workflow; Crowdsourcing; Automation; Citizen science; Quality (philosophy); Data quality; Outsourcing","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":[],"consensus_categories":[],"category_scores_codex":[0.02675538,0.001278445,0.0007866597,0.004299576,0.001217445,0.005644258,0.002916865,0.001855519,0.007015123],"category_scores_gemma":[0.08454473,0.0004835081,0.001555737,0.003784217,0.00208874,0.004615564,0.007888774,0.001281816,0.001893147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002287811,"about_ca_system_score_gemma":0.001904666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008125393,"about_ca_topic_score_gemma":0.009098792,"domain_scores_codex":[0.9828827,0.01107952,0.001119623,0.001286683,0.003047985,0.0005833505],"domain_scores_gemma":[0.9437099,0.0386271,0.002299206,0.007700881,0.005883173,0.001779767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.008794637,0.003671418,0.08118804,0.009705461,0.00126722,0.0005720068,0.02995542,0.03134319,0.01270826,0.01549796,0.088219,0.7170774],"study_design_scores_gemma":[0.004157744,0.01434968,0.2974085,0.005337731,0.001519438,0.001891488,0.03427191,0.2421974,0.02999475,0.05074938,0.3162634,0.001858599],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7765023,0.001540394,0.1129794,0.001763447,0.0006870645,0.007654164,0.01795443,0.02949143,0.05142746],"genre_scores_gemma":[0.7354463,0.000632474,0.2320431,0.0006702472,0.00008822148,0.005537895,0.01707363,0.003721608,0.004786653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02675538,"threshold_uncertainty_score":0.1414977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3281831222620335,"score_gpt":0.3980828804155645,"score_spread":0.069899758153531,"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."}}