{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01138524,0.0001665668,0.0002960119,0.003498807,0.002116072,0.005356026,0.0008508936,0.0006203011,0.005815776],"category_scores_gemma":[0.1136494,0.0002136745,0.0001975687,0.007135491,0.001396005,0.00351619,0.003278958,0.0008899154,0.0007276641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358294,"about_ca_system_score_gemma":0.002088699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004390121,"about_ca_topic_score_gemma":0.01217752,"domain_scores_codex":[0.9923955,0.004135243,0.0004746257,0.0007050878,0.001682356,0.0006071018],"domain_scores_gemma":[0.7826732,0.1530731,0.02818071,0.0108081,0.01614903,0.009115806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001374544,0.0002251361,0.8463242,0.0003048326,0.00005554903,0.0001890073,0.03917761,0.0005838934,0.0005842666,0.01358173,0.00866442,0.09017194],"study_design_scores_gemma":[0.0000419616,0.0002004424,0.7624048,0.0006578262,0.0001202177,0.000671311,0.1244623,0.006752061,0.002164828,0.01999343,0.08242715,0.0001036569],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9528357,0.0004155928,0.008725909,0.003872607,0.0001359947,0.0001345036,0.0005305508,0.00009921537,0.03325003],"genre_scores_gemma":[0.9934995,0.0003088462,0.002717942,0.0001719644,0.00008662546,0.00005367506,0.0002727376,0.00005612313,0.002832619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01138524,"threshold_uncertainty_score":0.06021166,"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."}}