{"id":"W2153258502","doi":"10.1109/icre.2003.1232745","title":"Improving requirements tracing via information retrieval","year":2004,"lang":"en","type":"article","venue":"Journal of Lightwave Technology","topic":"Software Engineering Research","field":"Computer Science","cited_by":290,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University; National Aeronautics and Space Administration","keywords":"Tracing; Traceability; Computer science; Framing (construction); Focus (optics); Information retrieval; Data mining; Software engineering; Programming language; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0006093599,0.00009616493,0.0001734202,0.001086711,0.00006360537,0.00008082215,0.000933696,0.0001540842,0.000003530856],"category_scores_gemma":[0.001078763,0.00008442492,0.00005896475,0.0009379298,0.0000399209,0.001685804,0.0002028384,0.0004916711,0.00003291079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002937898,"about_ca_system_score_gemma":0.000159365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000351316,"about_ca_topic_score_gemma":3.729178e-7,"domain_scores_codex":[0.9986568,0.00001142628,0.0004991575,0.0000966523,0.0004551341,0.0002808318],"domain_scores_gemma":[0.9988627,0.00007167298,0.0003415047,0.0003179898,0.000336224,0.00006992603],"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":[0.0001513562,0.0003511945,0.009076747,0.0002590751,0.0003030343,0.001080717,0.002955387,0.005117603,0.3858012,0.06063582,0.0006317665,0.5336361],"study_design_scores_gemma":[0.004176979,0.002196389,0.005597494,0.0003533944,0.00002758758,0.004247984,0.0001310253,0.005928112,0.9239933,0.0491875,0.003558783,0.0006014012],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2078502,0.0001003959,0.7896293,0.001720047,0.000430158,0.0000597369,1.784171e-7,0.0001690717,0.00004084014],"genre_scores_gemma":[0.897687,0.000009589015,0.1021782,0.00004343467,0.00006868999,7.403212e-7,1.647058e-7,0.000005554264,0.000006641252],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6898368,"threshold_uncertainty_score":0.3442748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136877547295464,"score_gpt":0.253957388270777,"score_spread":0.2425886127978223,"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."}}