{"id":"W2259025591","doi":"10.1016/j.jksuci.2012.10.002","title":"A high abstraction level approach for detecting feature interactions between telecommunication services","year":2012,"lang":"en","type":"article","venue":"Journal of King Saud University - Computer and Information Sciences","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Abstraction; Feature (linguistics); Computer science; Telecommunications; Telecommunications service; 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":[0.001053084,0.00007873101,0.0001181492,0.0004054612,0.0005546588,0.0003212695,0.0006305327,0.0000335003,0.000001112094],"category_scores_gemma":[0.000009166901,0.00007120216,0.00005543891,0.0004047096,0.00003743734,0.01183707,0.0001989793,0.0001541028,0.000001112728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001012773,"about_ca_system_score_gemma":0.00003715602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004262763,"about_ca_topic_score_gemma":0.000004749689,"domain_scores_codex":[0.9992247,0.00005480839,0.0002377001,0.00007667083,0.0002435239,0.0001626063],"domain_scores_gemma":[0.9988114,0.0001841741,0.0006215178,0.000126133,0.0001794661,0.00007735084],"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":[0.00003015789,0.00007932024,0.009564822,0.0001698015,0.0001160349,5.439942e-7,0.007550639,0.05580399,0.00005310247,0.01593217,0.001204114,0.9094953],"study_design_scores_gemma":[0.001090767,0.000382738,0.1847436,0.0001576186,0.00008137573,0.00009923701,0.003667088,0.7079117,0.000272304,0.0002431514,0.1009988,0.0003516924],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06319494,0.00002457411,0.9355145,0.0003863992,0.0003654231,0.0001148129,0.000002097441,0.0000227916,0.000374538],"genre_scores_gemma":[0.6907045,0.00002343127,0.3089803,0.0001304364,0.0001475476,2.788449e-7,0.000003747695,9.769738e-7,0.000008763378],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9091436,"threshold_uncertainty_score":0.8581588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03523602253372856,"score_gpt":0.2491124164896787,"score_spread":0.2138763939559502,"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."}}