{"id":"W2154234176","doi":"10.1109/spcon.1994.344417","title":"Elicit: a method for eliciting process models","year":2002,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Process (computing); Dependency (UML); Software engineering; Software; Scale (ratio); Reverse engineering; Product (mathematics); Programming language; 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":[0.0085516,0.00258429,0.001200242,0.00292747,0.001543022,0.003497295,0.002794309,0.003269191,0.01837702],"category_scores_gemma":[0.02827126,0.001882065,0.002378308,0.002586029,0.001481076,0.006501457,0.004778235,0.004243285,0.008883908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001391627,"about_ca_system_score_gemma":0.003180231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001831813,"about_ca_topic_score_gemma":0.003263141,"domain_scores_codex":[0.9860822,0.00620732,0.001373212,0.001618915,0.004402712,0.0003156233],"domain_scores_gemma":[0.977986,0.01438239,0.001160991,0.003950738,0.002177334,0.0003425774],"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":[0.0007036265,0.0003654614,0.001969656,0.002795249,0.0002345934,0.0008608068,0.005072016,0.02356553,0.02945406,0.2377453,0.05584684,0.6413868],"study_design_scores_gemma":[0.0003620605,0.0002780944,0.0006829062,0.0006611898,0.0001610274,0.001772648,0.0009376489,0.2254885,0.03546815,0.2007855,0.5331241,0.0002783053],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002826967,0.00002628353,0.9957538,0.00007952055,0.0000183848,0.0001874274,0.0003223855,0.002527797,0.0008018219],"genre_scores_gemma":[0.009621866,0.0001254973,0.9832681,0.0001168484,0.00002471467,0.001271562,0.001466595,0.000928277,0.003176625],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01837702,"threshold_uncertainty_score":0.0614773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07048182757300119,"score_gpt":0.345250638686727,"score_spread":0.2747688111137258,"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."}}