{"id":"W2003127245","doi":"10.1007/s00165-010-0158-z","title":"Partial order semantics for use case and task models","year":2010,"lang":"en","type":"article","venue":"Formal Aspects of Computing","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Notation; Semantics (computer science); Task (project management); Semantic data model; Programming language; Artificial intelligence","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":[0.0004434757,0.0001272962,0.0001979189,0.00006888123,0.0001370726,0.00007617267,0.0002652365,0.00006262124,3.072624e-7],"category_scores_gemma":[0.0005861986,0.0001205614,0.00003916203,0.0001503519,0.00005521491,0.001035095,0.000375775,0.0001808818,3.633632e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000605699,"about_ca_system_score_gemma":0.00002934906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001141481,"about_ca_topic_score_gemma":0.000007104635,"domain_scores_codex":[0.9990871,0.00001917907,0.0002302762,0.0002248256,0.0001080013,0.0003305983],"domain_scores_gemma":[0.9983853,0.0009883255,0.0001118916,0.0003019336,0.0001480025,0.00006462205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001182745,0.0000317865,0.00008931391,0.0001140497,0.00002475675,0.0001157879,0.001510006,0.4321854,0.002200479,0.5123795,0.00001768559,0.05131943],"study_design_scores_gemma":[0.0002721022,0.00008129173,0.00009149045,0.00001443334,0.000006156442,0.000503287,0.00002071338,0.959603,0.004674839,0.03447245,0.000104242,0.0001559594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2782796,0.00001602861,0.720951,0.00003081658,0.0003983474,0.0001175139,0.000002345055,0.0001779134,0.00002646598],"genre_scores_gemma":[0.4992296,7.346599e-7,0.5006959,0.00001302759,0.00005032665,0.00000125848,4.30869e-7,0.000006196575,0.000002541899],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5274177,"threshold_uncertainty_score":0.491635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03965073029926559,"score_gpt":0.2887629582571282,"score_spread":0.2491122279578626,"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."}}