{"id":"W2969850002","doi":"","title":"VOLUNTEERING GEOGRAPHIC INFORMATION TO AUTHORITATIVE DATABASES: LINKING CONTRIBUTOR MOTIVATIONS TO PROGRAM CHARACTERISTICS","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Volunteered geographic information; Geography; Data science; Database; World Wide Web; Cartography; Information retrieval; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001222945,0.0001720039,0.000301385,0.0005445098,0.0007583193,0.0003268187,0.0002933319,0.00007115123,0.0001109165],"category_scores_gemma":[0.001470847,0.0001744029,0.00007628654,0.001354599,0.00007169977,0.001333766,0.0001667959,0.0001343903,0.002149135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001055238,"about_ca_system_score_gemma":0.00009310859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008710254,"about_ca_topic_score_gemma":0.0002971605,"domain_scores_codex":[0.997829,0.00008575613,0.0006830554,0.000167154,0.0006772477,0.0005578228],"domain_scores_gemma":[0.99811,0.0002696613,0.0002499341,0.0003099697,0.0008188338,0.0002415755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004332444,0.0001497588,0.3064012,0.0005232746,0.000265949,0.000001749028,0.3928271,0.0001768598,0.00006934794,0.2562702,0.002981843,0.04028939],"study_design_scores_gemma":[0.0003959671,0.0001693788,0.3124484,0.0005014158,0.00003406031,0.000001196968,0.05478927,0.0007574105,0.000013184,0.0003499514,0.6300377,0.0005020144],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9251784,0.00001438322,0.03305036,0.004013948,0.001644765,0.006584838,0.0003718189,0.0008614692,0.02828],"genre_scores_gemma":[0.9867484,0.000006531946,0.01138216,0.0006562191,0.0001417126,0.0005445202,0.000177151,0.00001037584,0.000332927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6270559,"threshold_uncertainty_score":0.9986278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01804148182838048,"score_gpt":0.3098344495250032,"score_spread":0.2917929676966227,"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."}}