{"id":"W2896875458","doi":"10.1109/re.2018.00033","title":"Morse: Reducing the Feature Interaction Explosion Problem using Subject Matter Knowledge as Abstract Requirements","year":2018,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Critical Systems Labs","funders":"","keywords":"Feature (linguistics); Computer science; Domain (mathematical analysis); Risk analysis (engineering); Simple (philosophy); Subject-matter expert; Point (geometry); Artificial intelligence; Human–computer interaction; Data science; Expert system; Mathematics","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":[0.006000444,0.001741547,0.001471965,0.003313525,0.001069137,0.002270971,0.002595688,0.001862349,0.005964862],"category_scores_gemma":[0.04032008,0.001563593,0.004353452,0.00128309,0.002538853,0.00587549,0.005971614,0.003980067,0.001129036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00122914,"about_ca_system_score_gemma":0.002764288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003706584,"about_ca_topic_score_gemma":0.005698486,"domain_scores_codex":[0.9900073,0.002653239,0.0005899417,0.001315937,0.004823856,0.0006096457],"domain_scores_gemma":[0.9676982,0.0212993,0.001985352,0.006035673,0.002592218,0.0003893292],"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":[0.0007068462,0.0008204249,0.008377445,0.001373391,0.0004302975,0.002309111,0.001961397,0.1850182,0.03070724,0.1754194,0.01074068,0.5821356],"study_design_scores_gemma":[0.0001581129,0.0003250827,0.00159657,0.0002429925,0.0002549115,0.0006583586,0.0005385944,0.6915255,0.03580757,0.2475737,0.02119205,0.0001265065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01630928,0.00006722781,0.976977,0.0003144224,0.00002766354,0.0002693381,0.0002634461,0.002975243,0.002796308],"genre_scores_gemma":[0.1084435,0.0001057404,0.8868929,0.000261672,0.00003477444,0.000282346,0.0008921229,0.0007367202,0.002350322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006000444,"threshold_uncertainty_score":0.03173375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05720230423770137,"score_gpt":0.3512630367988539,"score_spread":0.2940607325611525,"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."}}