{"id":"W2946747703","doi":"10.1145/3305160.3305161","title":"A Productivity Framework for Software Development Literature Review","year":2019,"lang":"en","type":"article","venue":"","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Productivity; Assertion; Computer science; Context (archaeology); Measure (data warehouse); Software; Software development; Work (physics); Productivity model; Engineering; Data mining; Total factor productivity; Economics","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":[0.0004128086,0.0001051133,0.0001387667,0.00003363923,0.00003847623,0.0001084902,0.0004755369,0.00006015648,0.00002501576],"category_scores_gemma":[0.0005280466,0.00008202361,0.00004474815,0.0003011172,0.000003161927,0.000518035,0.0001254938,0.0001443794,0.00004185283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001949025,"about_ca_system_score_gemma":0.00004850763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.195559e-7,"about_ca_topic_score_gemma":1.641809e-7,"domain_scores_codex":[0.9992601,0.00001618264,0.0001223492,0.0003126822,0.000128047,0.000160645],"domain_scores_gemma":[0.9989538,0.0003025022,0.00005359534,0.0005585161,0.00009325127,0.00003837956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000695143,0.00008676124,0.0009772972,0.005508158,0.00004058141,0.000005610874,0.0004514404,0.00002318602,0.00002372394,0.1795559,0.02936189,0.7839585],"study_design_scores_gemma":[0.00006608534,0.00008199706,0.0006280104,0.003910482,0.000005148575,0.00002864814,7.229927e-7,0.0003198602,0.001674952,0.01445645,0.9785129,0.0003147448],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001211161,0.01304701,0.9834366,0.001453102,0.0002945541,0.000626445,7.343761e-7,0.0009018529,0.0001185241],"genre_scores_gemma":[0.001198077,0.0009167178,0.995887,0.0009614522,0.00004582056,0.0001239438,0.00000304938,0.000008445141,0.0008554818],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.949151,"threshold_uncertainty_score":0.3344826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01444983839340858,"score_gpt":0.2800131099364815,"score_spread":0.265563271543073,"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."}}