{"id":"W1882295992","doi":"10.1109/nafips.2001.944298","title":"Evaluating software project similarity by using linguistic quantifier guided aggregations","year":2002,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Quantifier (linguistics); Software; Similarity (geometry); Set (abstract data type); Fuzzy logic; Natural language processing; Fuzzy set; Artificial intelligence; Programming language; Linguistics; Software 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0006893869,0.0001606158,0.000153154,0.0001805097,0.0002667553,0.0002996426,0.0007871942,0.00007623094,0.0001395054],"category_scores_gemma":[0.0113675,0.0001562872,0.00006120146,0.0008731948,0.00003982016,0.0002741648,0.0002887416,0.0002414964,0.00008256027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001260631,"about_ca_system_score_gemma":0.0001113475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002197047,"about_ca_topic_score_gemma":0.000004523789,"domain_scores_codex":[0.9980083,0.00009627881,0.0002893601,0.0004864415,0.0006634087,0.0004562642],"domain_scores_gemma":[0.9977055,0.001039905,0.00006192846,0.000751385,0.0003423602,0.00009894448],"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":[0.00001345442,0.001660586,0.08062009,0.0008448593,0.000458425,0.0003396532,0.01520383,0.07526608,0.0321087,0.01513404,0.3663138,0.4120365],"study_design_scores_gemma":[0.0002017598,0.00004223709,0.0002395687,0.00003973215,0.000006594277,0.00002217649,0.000005737583,0.9956839,0.001636293,0.0002758345,0.001612695,0.0002334545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05585608,0.0002984953,0.9415832,0.0001719209,0.0003782318,0.0003338231,0.000004390567,0.0009551313,0.0004187203],"genre_scores_gemma":[0.3591343,0.000006699776,0.6390828,0.0001199085,0.0001032287,0.00002574442,0.000004581711,0.00002642414,0.001496348],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9204178,"threshold_uncertainty_score":0.9969602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2227936502049607,"score_gpt":0.4081115223958022,"score_spread":0.1853178721908416,"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."}}