{"id":"W2781488941","doi":"10.1007/978-981-10-7796-8_2","title":"An Empirical Study of the Software Development Process, Including Its Requirements Engineering, at Very Large Organization: How to Use Data Mining in Such a Study","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Process (computing); Computer science; Software; Empirical research; Focus (optics); Data science; Software engineering","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":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.002086895,0.0002131934,0.0002420604,0.001009143,0.0004791949,0.0006062973,0.007954756,0.00007100488,0.000003792159],"category_scores_gemma":[0.001197618,0.0001924878,0.00000935295,0.001841464,0.0001035064,0.007149302,0.01414045,0.0002918657,0.000007399883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003562261,"about_ca_system_score_gemma":0.000482138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005136756,"about_ca_topic_score_gemma":0.0000935379,"domain_scores_codex":[0.9975531,0.00005915399,0.0006597818,0.0004525279,0.0009948427,0.0002806452],"domain_scores_gemma":[0.9947715,0.0003752694,0.0002212597,0.00373088,0.0007955751,0.0001054975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007733017,0.0007897602,0.7765176,0.0001408924,0.00003856724,0.000002655305,0.2040557,0.004758659,0.000007320182,0.0004843212,0.0004050452,0.01279186],"study_design_scores_gemma":[0.0009381491,0.0003422752,0.6488277,0.0005518805,0.000007839972,0.00001044596,0.0007165773,0.3416145,0.00003779616,0.00001173667,0.006389149,0.000551946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7480632,0.00003962921,0.2488489,0.0001994364,0.0003429342,0.002232645,0.00001841473,0.000168805,0.00008601727],"genre_scores_gemma":[0.9381031,0.00001445572,0.06161649,0.0000874779,0.0000141192,0.00003650251,0.00003481946,0.00001356425,0.00007944959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3368558,"threshold_uncertainty_score":0.9974127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1590360050690562,"score_gpt":0.379249727736557,"score_spread":0.2202137226675008,"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."}}