{"id":"W3163016207","doi":"10.1145/1082983.1082958","title":"Decision support for customization of the COTS selection process","year":2005,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Personalization; Exploit; Computer science; Process (computing); Context (archaeology); Domain (mathematical analysis); Selection (genetic algorithm); Software engineering; Software; Systems engineering; Risk analysis (engineering); Process management; Engineering; Artificial intelligence; World Wide Web","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":[0.01159862,0.001126515,0.000856666,0.002457365,0.0008917115,0.003722513,0.001732687,0.001704284,0.00566739],"category_scores_gemma":[0.03520241,0.0006189069,0.0009654182,0.001297148,0.0008512216,0.00263939,0.001864963,0.001528789,0.0009410887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00109239,"about_ca_system_score_gemma":0.002112912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001854341,"about_ca_topic_score_gemma":0.002713709,"domain_scores_codex":[0.9902896,0.005007447,0.001043047,0.001266592,0.001932315,0.0004609232],"domain_scores_gemma":[0.9606661,0.0289902,0.003355669,0.003734227,0.002681755,0.0005721491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006184836,0.000967993,0.008341474,0.000739113,0.0001588499,0.0009724681,0.001636271,0.2270816,0.02008725,0.02972422,0.00325952,0.7064127],"study_design_scores_gemma":[0.000280685,0.0003661972,0.003745548,0.000358556,0.0001419674,0.0003317256,0.0007129537,0.9228134,0.01946342,0.03926617,0.01236873,0.0001507221],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06318652,0.0002031215,0.9257904,0.0008782835,0.00003838983,0.0006668331,0.0001643553,0.002511748,0.006560374],"genre_scores_gemma":[0.5341086,0.0002077273,0.4636518,0.0001246198,0.00003317029,0.0002542584,0.0003077631,0.00009140259,0.001220633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01159862,"threshold_uncertainty_score":0.06134009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02178613476656997,"score_gpt":0.2901775556408728,"score_spread":0.2683914208743028,"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."}}