{"id":"W2032557572","doi":"10.5555/2820282.2820313","title":"Make it simple: an empirical analysis of GNU make feature use in open source projects","year":2015,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Queen's University","funders":"","keywords":"Computer science; Scripting language; Programming language; Macro; Popularity; Open source; Set (abstract data type); Simple (philosophy); Implementation; Simplicity; Feature (linguistics); Function (biology); Focus (optics); Software engineering; World Wide Web; Software; Linguistics","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":[0.01118848,0.0003769139,0.0004322932,0.00644346,0.001048604,0.002831436,0.001201899,0.00135145,0.002227003],"category_scores_gemma":[0.1333248,0.0004332617,0.0005470216,0.006656018,0.002548026,0.005515334,0.003072589,0.001725879,0.0009542229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006492504,"about_ca_system_score_gemma":0.000360179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001740502,"about_ca_topic_score_gemma":0.002205195,"domain_scores_codex":[0.986675,0.005277005,0.001284229,0.001996428,0.004065557,0.0007018951],"domain_scores_gemma":[0.7170713,0.1832743,0.06285916,0.01554871,0.01522558,0.006021079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001770079,0.000155963,0.9779035,0.0001193488,0.0001176495,0.000169953,0.00638903,0.0003403548,0.0005892362,0.0003067132,0.0009766917,0.01275453],"study_design_scores_gemma":[0.000007066491,0.0001185837,0.9903291,0.00007492602,0.00002139948,0.0004084996,0.005722275,0.001326632,0.0003604429,0.0002118139,0.001385965,0.00003322439],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984188,0.0001329126,0.0003439566,0.00009199889,0.000005337856,0.00001506249,0.0002959721,0.00003908439,0.0006567608],"genre_scores_gemma":[0.9983168,0.00008637378,0.0004601151,0.00003190878,0.00001021546,0.00003709166,0.0006707649,0.00007295319,0.0003136596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01118848,"threshold_uncertainty_score":0.05917102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1270107041835635,"score_gpt":0.3841988980037417,"score_spread":0.2571881938201782,"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."}}