{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005523944,0.0006008922,0.0004490825,0.005677712,0.0007328172,0.001187539,0.0005766098,0.0004219417,0.00381761],"category_scores_gemma":[0.02393305,0.0003666736,0.001534216,0.003565771,0.0004620747,0.0009992422,0.00116363,0.0006196154,0.000320462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001834506,"about_ca_system_score_gemma":0.001981925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003697233,"about_ca_topic_score_gemma":0.003262854,"domain_scores_codex":[0.9916415,0.002166477,0.0006392887,0.0005263183,0.004567941,0.0004584166],"domain_scores_gemma":[0.9683372,0.02245256,0.004742533,0.0009072361,0.003076622,0.000483901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005500281,0.0003556732,0.7307236,0.0007337388,0.0005742725,0.001260584,0.002220165,0.1236835,0.00287185,0.01017863,0.001304888,0.1255431],"study_design_scores_gemma":[0.00005014678,0.001341383,0.6862364,0.0003290664,0.0006301202,0.002201161,0.003935409,0.2798236,0.006625609,0.01010531,0.008578097,0.0001436579],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9682876,0.0003077422,0.02173513,0.0001081139,0.000006740163,0.0003469291,0.001028729,0.00009173981,0.008087251],"genre_scores_gemma":[0.9881452,0.0002571753,0.009266661,0.00001306498,0.000006415597,0.0001443524,0.001042931,0.00001758014,0.001106632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005677712,"threshold_uncertainty_score":0.02921379,"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."}}