{"id":"W2078515278","doi":"10.5555/2820282.2820288","title":"Detection of software evolution phases based on development activities","year":2015,"lang":"en","type":"article","venue":"International Conference on Program Comprehension","topic":"Software Engineering Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Software evolution; Computer science; Software development; Granularity; Software; Software construction; Commit; Software engineering; Software sizing; Software analytics; Software metric; Software maintenance; Data mining; Database; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002167108,0.0001563369,0.0001382329,0.0003851978,0.00005626544,0.0001156913,0.0006048962,0.00006651827,0.00001514014],"category_scores_gemma":[0.0003774534,0.0001475566,0.00004763296,0.0002442578,0.00005056098,0.0002708258,0.0001363406,0.0001795224,0.00002835613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003078496,"about_ca_system_score_gemma":0.0002892482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000176264,"about_ca_topic_score_gemma":0.000005201187,"domain_scores_codex":[0.9981244,0.000060279,0.0002297355,0.0003391824,0.001049164,0.0001972882],"domain_scores_gemma":[0.9985854,0.0003051653,0.0001015702,0.0003251196,0.0005732733,0.0001094532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004365323,0.001583567,0.005900269,0.00004686834,0.00006190487,0.00001710422,0.0003989236,0.01868238,0.01322654,0.01242589,0.0002221968,0.9469978],"study_design_scores_gemma":[0.00158903,0.002084597,0.02317704,0.0004344802,0.000004226262,0.000009278866,0.00007122026,0.8482015,0.1177033,0.001343788,0.004962064,0.000419438],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.353552,0.00001605034,0.6440591,0.0001742579,0.0008592369,0.0003094939,0.000002916046,0.00055848,0.0004684085],"genre_scores_gemma":[0.9542663,9.165129e-7,0.04550086,0.00002899339,0.00003548214,0.00008617368,0.00001425209,0.00000974907,0.00005732129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9465784,"threshold_uncertainty_score":0.6017185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08285909543163568,"score_gpt":0.3309184893314647,"score_spread":0.2480593938998291,"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."}}