{"id":"W2152570911","doi":"10.5121/ijsea.2010.1301","title":"Bayesian Network Based XP Process Modelling","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Engineering & Applications","topic":"Software Engineering Research","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Extreme programming; Bayesian network; Computer science; Process (computing); Software; Software development; Machine learning; Software development process; Programming language","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":[0.002586223,0.001082878,0.001368146,0.002194953,0.0006492037,0.002423029,0.002733092,0.002864529,0.006056595],"category_scores_gemma":[0.009380765,0.001042426,0.00125459,0.002661338,0.0009025069,0.002626667,0.001046316,0.001974381,0.00131832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002300978,"about_ca_system_score_gemma":0.001484879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02365805,"about_ca_topic_score_gemma":0.01252325,"domain_scores_codex":[0.9979615,0.000783676,0.0001152641,0.0003958617,0.000577093,0.0001665889],"domain_scores_gemma":[0.9959944,0.002752094,0.0004289693,0.0001188852,0.0006330158,0.00007263828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003145578,0.00002556455,0.0004688863,0.00003821944,0.00002474282,0.00007232041,0.0000456573,0.9703621,0.0002460931,0.02080656,0.0003775996,0.007500733],"study_design_scores_gemma":[0.000006744609,0.000006623328,0.0001047701,0.000005769916,0.000007801643,0.00001315604,0.000003570558,0.9937748,0.0000627845,0.005596738,0.0004112338,0.000005913324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01370359,0.0003267034,0.9765705,0.0003817398,0.00004433471,0.0001361148,0.0006433138,0.0003810992,0.007812563],"genre_scores_gemma":[0.7398399,0.002115767,0.2267613,0.0002235229,0.0001199288,0.001464141,0.002117295,0.0001650141,0.02719302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02365805,"threshold_uncertainty_score":0.04704064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008758295651533717,"score_gpt":0.2609209078791803,"score_spread":0.2521626122276466,"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."}}