{"id":"W2229929634","doi":"","title":"Reducing Global Poverty and Disease with Community and Technology: An Open Source Perspective","year":2008,"lang":"en","type":"article","venue":"˜The œopen source business resource","topic":"ICT in Developing Communities","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Poverty; Perspective (graphical); Open source; Development economics; Computer science; Economic growth; Economics; Artificial intelligence; Software","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":["open_science"],"category_scores_codex":[0.0009034344,0.0004464883,0.0004872532,0.0001703982,0.004213618,0.001870477,0.008605557,0.0001371325,0.000005452645],"category_scores_gemma":[0.000217748,0.0003320097,0.00002225351,0.002060516,0.001510528,0.001524377,0.01504109,0.0006528176,0.000006930102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002180289,"about_ca_system_score_gemma":0.0005126542,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009792364,"about_ca_topic_score_gemma":0.0006079231,"domain_scores_codex":[0.9971698,0.000862301,0.0003076982,0.0006603311,0.0004240065,0.0005758806],"domain_scores_gemma":[0.9956635,0.0002793706,0.0002518301,0.002935467,0.0005511828,0.0003186832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.003985378,0.004189288,0.2894553,0.0007072332,0.001226789,0.0008994527,0.3477097,0.0107269,0.0003474413,0.1196276,0.03504449,0.1860805],"study_design_scores_gemma":[0.00730127,0.001044882,0.4529625,0.001786969,0.0002232798,0.006764596,0.08754127,0.03546825,0.00009074894,0.02955926,0.3731013,0.004155664],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8998249,0.001024779,0.06546997,0.01992215,0.00007502146,0.001693817,0.00002039304,0.0007824512,0.01118651],"genre_scores_gemma":[0.9859526,0.00003991048,0.008664119,0.003258838,0.00005309703,0.00008835174,0.00001309394,0.00006190862,0.001868078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3380568,"threshold_uncertainty_score":0.9999132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03068800243587662,"score_gpt":0.270211909141651,"score_spread":0.2395239067057744,"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."}}