{"id":"W4313573246","doi":"10.3390/jrfm16010033","title":"Analysis of 105 IT Project Risks","year":2023,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Technology Assessment and Management","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Project risk management; Executor; Project manager; Risk analysis (engineering); Project management; Project team; Risk management; Risk management plan; Business; Maturity (psychological); Operations management; Process management; IT risk management; Project management triangle; Computer science; Engineering; Knowledge management; Finance; Systems engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0004168146,0.00009540062,0.0002934782,0.001404228,0.00003894848,0.0000128609,0.0001443602,0.0000522046,0.00001164043],"category_scores_gemma":[0.00001763639,0.00008433905,0.0001363169,0.001420338,0.00002797678,0.0000783874,0.00008258761,0.0001407562,0.000003512206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002229809,"about_ca_system_score_gemma":0.000005569545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001393021,"about_ca_topic_score_gemma":0.00003053115,"domain_scores_codex":[0.9992318,0.00001390374,0.0003526223,0.00008124186,0.0001713208,0.0001491383],"domain_scores_gemma":[0.9996465,0.00002446054,0.0001508176,0.0001258164,0.00003014486,0.00002226173],"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":[0.00005614748,0.0000916812,0.05169871,0.0002579002,0.002447082,0.0001979034,0.0008349048,0.02347248,0.0000370651,0.01078636,0.03729493,0.8728248],"study_design_scores_gemma":[0.0007429243,0.0001485367,0.8005606,0.00005318453,0.002899997,0.000001597262,0.0009974854,0.006935889,0.00006221201,0.001628034,0.1857832,0.0001863866],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9220578,0.0005843365,0.07197485,0.000128689,0.0006188582,0.0002411655,0.00002067919,0.0001504675,0.004223169],"genre_scores_gemma":[0.9887688,0.01002579,0.001011616,0.00001397323,0.00003901338,0.000005606524,0.000002853715,0.00000827636,0.0001241003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8726385,"threshold_uncertainty_score":0.3439247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01477996487441772,"score_gpt":0.2642073847250981,"score_spread":0.2494274198506804,"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."}}