{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00779913,0.0003844922,0.0006062285,0.001725739,0.001694335,0.001873209,0.0007907769,0.001005539,0.003594938],"category_scores_gemma":[0.0397984,0.0006155734,0.0002953286,0.001581293,0.001100393,0.00245137,0.001443224,0.002084311,0.0004875754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008465656,"about_ca_system_score_gemma":0.002010059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002833171,"about_ca_topic_score_gemma":0.002964386,"domain_scores_codex":[0.9950601,0.002378226,0.0003950904,0.0002935469,0.001093975,0.0007789624],"domain_scores_gemma":[0.9236609,0.05185054,0.01185071,0.00161371,0.006743368,0.004280732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000456495,0.008368162,0.8187312,0.0006832399,0.00007105082,0.0009828901,0.1338767,0.0002416757,0.001117808,0.0009463397,0.001081253,0.03344323],"study_design_scores_gemma":[0.00009807052,0.003726634,0.72702,0.0005842028,0.0001001386,0.0009291018,0.2592537,0.001669829,0.0008376007,0.0005720865,0.0051416,0.00006688684],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992318,0.00005511796,0.0001291726,0.00007598202,0.000001832694,0.00005574805,0.00002479322,0.000001436917,0.000424054],"genre_scores_gemma":[0.9989529,0.000176616,0.0003222298,0.0001007033,0.000005720023,0.0001267153,0.00005221372,0.000002863897,0.000260086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00779913,"threshold_uncertainty_score":0.04124624,"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."}}