{"id":"W6891789831","doi":"10.48550/arxiv.1007.5115","title":"Bayesian Network Based XP Process Modelling","year":2010,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Bayesian network; Extreme programming; Process (computing); Software; Dynamic Bayesian network; Bayesian probability; Software development","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":[0.002764394,0.001079846,0.001331583,0.002279713,0.0006428433,0.002514906,0.002618558,0.002840218,0.006279312],"category_scores_gemma":[0.01056757,0.00102643,0.001282347,0.002878065,0.001004101,0.002749369,0.001123716,0.002141885,0.00132425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002369368,"about_ca_system_score_gemma":0.001420538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02223657,"about_ca_topic_score_gemma":0.01181284,"domain_scores_codex":[0.9979091,0.0008339141,0.0001110271,0.0004227514,0.0005566064,0.0001666342],"domain_scores_gemma":[0.9954177,0.003259859,0.0004473839,0.0001435713,0.00064871,0.00008275992],"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":[0.00003452544,0.00002631853,0.0005630755,0.00004145575,0.00002803811,0.00007995051,0.00005532071,0.958734,0.000265918,0.0314106,0.0004765463,0.008284332],"study_design_scores_gemma":[0.000006671052,0.000006594923,0.0001156162,0.00000663254,0.000008459961,0.00001432347,0.000004210844,0.9903521,0.00006681408,0.008900856,0.000511502,0.000006185828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01333718,0.0003746619,0.9770269,0.0004401605,0.00004416817,0.0001192181,0.0006856613,0.0003546288,0.007617522],"genre_scores_gemma":[0.7388102,0.002439434,0.2269408,0.0002454768,0.0001354525,0.001264898,0.002238742,0.0001771418,0.02774785],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02223657,"threshold_uncertainty_score":0.04421431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06038898811416872,"score_gpt":0.1958923771792231,"score_spread":0.1355033890650544,"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."}}