{"id":"W2912612993","doi":"10.5539/cis.v12n1p59","title":"Feature Models Preconfiguration Based on User Profiling","year":2019,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Profiling (computer programming); Computer science; Software; Feature model; Software product line; Feature (linguistics); User requirements document; Software engineering; Data mining; Human–computer interaction; Software development","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005863454,0.00009256754,0.00008683619,0.000248832,0.0001132398,0.0003839124,0.0005080008,0.0000354133,0.00000119505],"category_scores_gemma":[0.00006842134,0.00007705834,0.00001643368,0.0004991961,0.00005175021,0.01251039,0.0001248425,0.0001048196,0.00003241668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003390561,"about_ca_system_score_gemma":0.00007611745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.63595e-7,"about_ca_topic_score_gemma":1.543183e-8,"domain_scores_codex":[0.9991728,0.00001940086,0.0001226416,0.0001980079,0.0003123757,0.0001747467],"domain_scores_gemma":[0.9992241,0.000151709,0.00006863211,0.0003494994,0.0001495873,0.00005650544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002481686,0.00000278951,0.00006947713,0.00001654314,5.45308e-7,9.453599e-8,0.0002971915,0.8828744,0.0001660612,0.06982621,0.00006008024,0.04668408],"study_design_scores_gemma":[0.0001471917,0.00006965424,0.001590112,0.00001958751,3.436203e-7,0.000003061157,0.000006615857,0.9927087,0.003002282,0.001293625,0.001052606,0.0001062143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005460016,0.00000612295,0.9914966,0.0002940102,0.0006162058,0.0001919064,8.100162e-7,0.0002400753,0.001694258],"genre_scores_gemma":[0.2167618,0.000003136506,0.7822894,0.0008929328,0.00001817147,0.000006190082,0.000002295785,0.000001864119,0.00002417239],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2113018,"threshold_uncertainty_score":0.9069729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02110567316289229,"score_gpt":0.256623008577113,"score_spread":0.2355173354142207,"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."}}