{"id":"W2136741769","doi":"10.1080/02681102.2015.1081868","title":"Viscous Open Data: The Roles of Intermediaries in an Open Data Ecosystem","year":2015,"lang":"en","type":"article","venue":"Information Technology for Development","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Intermediary; Open data; Business; Ecosystem; Environmental resource management; Knowledge management; Computer science; World Wide Web; Marketing; Environmental science; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["open_science"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["open_science"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"commentary","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0227096,0.0005964064,0.0006883971,0.005787537,0.01017598,0.03689556,0.001914936,0.004768734,0.005675414],"category_scores_gemma":[0.03277442,0.001002797,0.0009056962,0.008539787,0.02803136,0.05970064,0.02380626,0.006629572,0.001043414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006534837,"about_ca_system_score_gemma":0.01287056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004480815,"about_ca_topic_score_gemma":0.003971283,"domain_scores_codex":[0.9797319,0.01241357,0.001151454,0.00168546,0.003520552,0.001497115],"domain_scores_gemma":[0.942494,0.03757561,0.005571983,0.007082655,0.003513911,0.003761977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003503804,0.00003377886,0.006011124,0.0001117891,0.00002018902,0.0004876974,0.01311663,0.0006114841,0.0003744448,0.9590154,0.001735901,0.01844658],"study_design_scores_gemma":[0.00002374476,0.00005476543,0.002767976,0.0008881828,0.00004977839,0.0006088315,0.0290735,0.005701219,0.0009883088,0.7937955,0.1659678,0.00008039961],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1870518,0.008318261,0.3412868,0.1431898,0.0008751187,0.0005227995,0.0006683119,0.0007510107,0.317336],"genre_scores_gemma":[0.93551,0.003412116,0.04717626,0.0025744,0.000369381,0.0002100656,0.0001799641,0.0001629608,0.01040488],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9980851,"threshold_uncertainty_score":0.1201013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1319685321627065,"score_gpt":0.3819785333272386,"score_spread":0.2500100011645321,"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."}}