{"id":"W3133561796","doi":"","title":"EEF-CAS: An Effort Estimation Framework with Customizable Attribute Selection","year":2013,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Software Engineering Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Flexibility (engineering); Process (computing); Estimation; Personalization; Set (abstract data type); Data mining; Software; Selection (genetic algorithm); Industrial engineering; Machine learning; Systems 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01366029,0.001548265,0.001287565,0.004526079,0.000832891,0.002601976,0.003539812,0.0012262,0.002727377],"category_scores_gemma":[0.02546593,0.0005788532,0.001940138,0.003258602,0.001174053,0.003641261,0.003230752,0.001799839,0.0005853413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001475286,"about_ca_system_score_gemma":0.003108683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009214924,"about_ca_topic_score_gemma":0.00940559,"domain_scores_codex":[0.9915082,0.00355248,0.0006381442,0.001429143,0.002514301,0.0003576786],"domain_scores_gemma":[0.9868565,0.006880071,0.00139921,0.001568511,0.002947586,0.0003481533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003608972,0.0004878014,0.02093201,0.0004413707,0.0004764852,0.0003848647,0.0009562153,0.2554687,0.002773781,0.1064665,0.009420394,0.6018311],"study_design_scores_gemma":[0.00005789808,0.0002201433,0.00376127,0.0001083021,0.0001051547,0.0002538104,0.000186506,0.9237912,0.001772277,0.05852633,0.01110507,0.0001120122],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002332969,0.00007891604,0.9956166,0.000106226,0.00001338019,0.0001495453,0.0001488248,0.0008568245,0.000696815],"genre_scores_gemma":[0.1241149,0.0001620973,0.873463,0.0001036379,0.00006091766,0.00046419,0.0007272924,0.0001121111,0.0007918961],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01366029,"threshold_uncertainty_score":0.07224333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05334393255199717,"score_gpt":0.3042723863367829,"score_spread":0.2509284537847858,"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."}}