{"id":"W2415363387","doi":"","title":"Potential of VGI as a Resource for SDIS in The North/South Context","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Volunteered geographic information; Pace; Geography; The Internet; Context (archaeology); Resource (disambiguation); World Wide Web; Computer science; Line (geometry); Cartography","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":[],"consensus_categories":[],"category_scores_codex":[0.0009520652,0.00005691166,0.0001542408,0.00007398764,0.0001866841,0.00003158146,0.0002464053,0.00004086227,0.00007882404],"category_scores_gemma":[0.0002340946,0.00004008269,0.00007898883,0.0002634379,0.0001303096,0.00008412652,0.0000286692,0.00004454751,0.0001543628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001132287,"about_ca_system_score_gemma":0.00004018655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001323734,"about_ca_topic_score_gemma":0.001806725,"domain_scores_codex":[0.9989904,0.00008995154,0.0002948997,0.00007307153,0.0003509784,0.0002006755],"domain_scores_gemma":[0.9993429,0.0002137329,0.0001533131,0.0001715309,0.00009789639,0.00002061302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004598796,0.00005177047,0.09357571,0.0001952396,0.0000626728,9.762385e-7,0.8055156,0.00004859843,0.000007181043,0.09449846,0.003728108,0.002269702],"study_design_scores_gemma":[0.000994485,0.0001190594,0.1415943,0.00008068472,0.000027981,0.000001847327,0.7216772,0.0001713243,0.000005302698,0.00353451,0.131625,0.0001682505],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9238318,0.00003431507,0.00008758686,0.001469704,0.0001067944,0.0008926462,0.00001439295,0.00001628317,0.0735465],"genre_scores_gemma":[0.9986919,0.000002116653,0.00006463814,0.000280502,0.00004363232,0.00005768531,0.000003706551,0.000002919569,0.0008528685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1278969,"threshold_uncertainty_score":0.2001098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01207230616471227,"score_gpt":0.2570078620977201,"score_spread":0.2449355559330079,"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."}}