{"id":"W85855971","doi":"","title":"Emerging Open Source Health Information Business Ecosystems in Resource-Poor Environments: the OpenMRS Experience","year":2010,"lang":"en","type":"article","venue":"The open source business resource","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Business; Open source; Ecosystem; Resource (disambiguation); Environmental resource management; Environmental planning; Knowledge management; Geography; Ecology; Computer science; Environmental science; Biology","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":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.009844825,0.0006640655,0.0007350246,0.0005273505,0.002365306,0.02324893,0.03308742,0.0001827557,0.0001305711],"category_scores_gemma":[0.00103291,0.0004565826,0.00008838413,0.004749212,0.0005012632,0.0407118,0.02440513,0.001165156,0.0003706756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002817528,"about_ca_system_score_gemma":0.0004136974,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01302423,"about_ca_topic_score_gemma":0.003563577,"domain_scores_codex":[0.991917,0.001575813,0.001562115,0.00139013,0.001975206,0.001579743],"domain_scores_gemma":[0.9916391,0.0008431879,0.001515774,0.005435843,0.0002129992,0.0003531059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008773824,0.001279223,0.006751608,0.0006197419,0.0002830789,0.0000974182,0.05143573,0.05148161,0.001292412,0.02212582,0.1169886,0.7467673],"study_design_scores_gemma":[0.001238037,0.00003633356,0.01203275,0.0001610042,0.00001021055,0.00007246258,0.00678814,0.02626575,0.00003622317,0.00004357256,0.9527501,0.0005654468],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07050383,0.0005291236,0.724283,0.1447218,0.001223884,0.01525843,0.00005170018,0.0005272308,0.04290097],"genre_scores_gemma":[0.9160977,0.0005774719,0.007022091,0.03573913,0.0009128221,0.003832255,0.000454824,0.0003366434,0.03502708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8455939,"threshold_uncertainty_score":0.9997886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04228284604437197,"score_gpt":0.326720693614056,"score_spread":0.284437847569684,"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."}}