{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009417236,0.0001354653,0.0003345451,0.0006785139,0.00002210962,0.0004007019,0.002102013,0.0001062454,0.0000225037],"category_scores_gemma":[0.001138424,0.0001132816,0.00006197128,0.004156033,0.00003113511,0.0005264611,0.001258992,0.0002668564,0.00001058236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009287523,"about_ca_system_score_gemma":0.0002808031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00128448,"about_ca_topic_score_gemma":0.003499046,"domain_scores_codex":[0.9981692,0.000137064,0.0002147771,0.0005023463,0.0006060541,0.000370556],"domain_scores_gemma":[0.9979586,0.0004547543,0.00004201589,0.001110869,0.0001874542,0.0002463092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002568679,0.0002208099,0.9532122,0.00001400217,0.0001561724,0.00006441271,0.00290457,0.01633354,0.00005861246,0.0004710814,0.01687453,0.009664376],"study_design_scores_gemma":[0.0006192802,0.0001931607,0.5434405,0.0000113958,0.00003275878,0.000008039031,0.0002194367,0.4409584,0.0003182584,0.00008992595,0.01383403,0.0002748223],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7582651,0.00001887227,0.2388758,0.001457394,0.00006511304,0.0004479754,0.000006161747,0.0002283047,0.0006352129],"genre_scores_gemma":[0.9265237,9.802078e-7,0.07003554,0.0003848127,0.0000216126,0.00002380611,0.00001467564,0.00001571974,0.002979104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4246248,"threshold_uncertainty_score":0.4619489,"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."}}