{"id":"W3013473881","doi":"10.19173/irrodl.v20i5.4345","title":"Value of Open Microcredentials to Earners and Issuers","year":2019,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Issuer; Reputation; Value (mathematics); Business; Marketing; Open education; Public relations; Knowledge management; Computer science; World Wide Web; Political science; Finance","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":[0.01642554,0.0002277962,0.0003779734,0.001362658,0.004543061,0.009305387,0.001002279,0.001487818,0.009060511],"category_scores_gemma":[0.04521411,0.0001815752,0.0002881973,0.001210878,0.004778326,0.007353643,0.007697165,0.002199452,0.0006355137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002519027,"about_ca_system_score_gemma":0.002905468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008017241,"about_ca_topic_score_gemma":0.002000962,"domain_scores_codex":[0.9738391,0.01725888,0.0005535403,0.000989378,0.005001151,0.00235799],"domain_scores_gemma":[0.9236032,0.04702155,0.009888811,0.004900043,0.005610953,0.008975487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004241099,0.001188788,0.1569105,0.0008517187,0.00008652027,0.004162325,0.2145624,0.0005683472,0.002918398,0.1117341,0.01404595,0.4925468],"study_design_scores_gemma":[0.00007151917,0.001601561,0.1328505,0.001717218,0.0001493054,0.002585724,0.5191726,0.001231832,0.003514566,0.0248383,0.3121114,0.0001555845],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.881624,0.001282803,0.004469075,0.0155988,0.0002403418,0.0001079751,0.00003754742,0.00008097306,0.09655859],"genre_scores_gemma":[0.9924567,0.000349778,0.0008377059,0.0006538572,0.0000758543,0.0000288834,0.00001189257,0.00001846937,0.005566914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01642554,"threshold_uncertainty_score":0.08686757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06895961078845728,"score_gpt":0.4608450084681361,"score_spread":0.3918853976796788,"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."}}