{"id":"W2008868354","doi":"10.1109/esem.2009.5316014","title":"Software risk management barriers: An empirical study","year":2009,"lang":"en","type":"article","venue":"","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Risk management; Risk perception; Risk analysis (engineering); Perception; IT risk management; Identification (biology); Factor analysis of information risk; Sample (material); Empirical research; Risk management plan; Computer science; Project risk management; Risk management information systems; Knowledge management; Business; Project management; Psychology; Program management; Engineering; Finance; Information system; Management information systems","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004130457,0.0001131945,0.00009509799,0.00008282468,0.0001066762,0.0002066944,0.000794851,0.00003318681,0.00004656161],"category_scores_gemma":[0.00007143286,0.00009433115,0.00003174461,0.0002783842,0.00000561512,0.0007485377,0.0001272646,0.000134534,0.00002673249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001944299,"about_ca_system_score_gemma":0.00001008813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001990942,"about_ca_topic_score_gemma":0.000002836311,"domain_scores_codex":[0.9990401,0.00007538896,0.0001316542,0.0003396676,0.0002249835,0.0001881556],"domain_scores_gemma":[0.9989756,0.00007186014,0.0000390152,0.0007386971,0.00002463388,0.0001502333],"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":[0.00001451096,0.0007246473,0.09057967,0.000006788003,0.00006704166,0.0002321496,0.002281539,0.0005493083,0.000001545531,0.01165131,0.01363385,0.8802577],"study_design_scores_gemma":[0.001633836,0.007953736,0.6718737,0.0000292471,0.0001275064,0.00006265676,0.001075333,0.05748517,0.0002621163,0.0727111,0.1849884,0.001797203],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02319894,0.00003091726,0.9721677,0.0002676043,0.0001123089,0.0002206099,4.140313e-7,0.002404371,0.001597081],"genre_scores_gemma":[0.442076,0.00001404927,0.5572307,0.0005014084,0.00002717431,0.000009869683,3.874331e-7,0.000004268233,0.0001361704],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8784605,"threshold_uncertainty_score":0.3846713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799088625763199,"score_gpt":0.3142956045484856,"score_spread":0.2963047182908536,"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."}}