{"id":"W4230500706","doi":"10.1002/spip.374","title":"Optimized mismatch resolution for COTS selection","year":2008,"lang":"en","type":"article","venue":"Software Process Improvement and Practice","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Process (computing); Selection (genetic algorithm); Reliability engineering; Software; Systems engineering; Computer science; Resource (disambiguation); Domain (mathematical analysis); Product (mathematics); Risk analysis (engineering); Engineering; Software engineering; Artificial intelligence; Operating system","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":[0.001059931,0.0001696534,0.0001832863,0.00009329747,0.0004266696,0.0001359568,0.0003098392,0.0001091776,0.000002881852],"category_scores_gemma":[0.001363975,0.0001637515,0.00004004169,0.0002888213,0.00003797776,0.002035834,0.00007746873,0.000137759,0.00000414574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006411455,"about_ca_system_score_gemma":0.0001477037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003783232,"about_ca_topic_score_gemma":0.000001753244,"domain_scores_codex":[0.998535,0.0001076234,0.0003051635,0.0004649044,0.0002990861,0.0002882557],"domain_scores_gemma":[0.9980934,0.0007420211,0.0003123573,0.0002441141,0.0005258878,0.00008218685],"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":[0.005266751,0.002583067,0.002431502,0.005203763,0.000864461,0.0001006189,0.03846628,0.0008019785,0.07040875,0.03560401,0.105002,0.7332668],"study_design_scores_gemma":[0.01572637,0.01107214,0.0004660303,0.000629804,0.0004615389,0.003786718,0.001794387,0.2402724,0.4376045,0.08359318,0.1999739,0.004619048],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001414358,0.0003883099,0.9947855,0.0009748234,0.0001684162,0.001040173,0.000003223298,0.0007820271,0.0004431113],"genre_scores_gemma":[0.126715,0.0001856929,0.8709362,0.0008026565,0.0001113503,0.0005977763,0.00000750044,0.0000223508,0.0006214711],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7286478,"threshold_uncertainty_score":0.6677593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03436764899921617,"score_gpt":0.3129931203933215,"score_spread":0.2786254713941053,"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."}}