{"id":"W2150306549","doi":"10.1109/ieem.2009.5373148","title":"A DEA evaluation of software project efficiency","year":2009,"lang":"en","type":"article","venue":"","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; York University","funders":"","keywords":"Data envelopment analysis; Productivity; Software; Computer science; Measure (data warehouse); Production (economics); Software project management; Software development; Software construction; Data mining; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01504937,0.0000899009,0.0002190879,0.0005278356,0.00009117457,0.00008336646,0.0006342583,0.00005524232,0.0005196462],"category_scores_gemma":[0.01427289,0.00006005274,0.0001458361,0.002485029,0.00006908341,0.0001677584,0.00003038432,0.00006375142,0.0001088571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006392834,"about_ca_system_score_gemma":0.0005033157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005139097,"about_ca_topic_score_gemma":0.00001989397,"domain_scores_codex":[0.9949187,0.0004460787,0.0006044481,0.0003690023,0.00344336,0.0002183981],"domain_scores_gemma":[0.9971857,0.0005987097,0.000244602,0.0006305266,0.001299886,0.00004059156],"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":[0.00003439886,0.0008605669,0.01725908,0.000003802042,0.00002021792,0.000003136851,0.002774082,0.0533262,0.006881949,0.007706224,0.01300547,0.8981249],"study_design_scores_gemma":[0.0008891706,0.0004737272,0.08821417,0.0000307621,0.0001978987,0.0000146756,0.001043978,0.7824043,0.009862693,0.1148094,0.001703897,0.0003553276],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8108699,0.0001586232,0.1566778,0.0004615581,0.00007161159,0.0002645713,0.00000193242,0.00006396615,0.03143004],"genre_scores_gemma":[0.9900154,0.000001060076,0.009070817,0.0002066095,0.0000192639,0.000002954925,9.208925e-7,0.000002774781,0.0006801416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8977696,"threshold_uncertainty_score":0.9940303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1841903640667518,"score_gpt":0.4599920540763076,"score_spread":0.2758016900095558,"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."}}