{"id":"W174591770","doi":"10.1007/978-3-642-28525-7_7","title":"A Logical Approach to Data-Aware Automated Sequence Generation","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Sequence (biology); Satisfiability; Set (abstract data type); Domain (mathematical analysis); Sequence diagram; Variety (cybernetics); Theoretical computer science; Programming language; Artificial intelligence; Unified Modeling Language; Software","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":[0.003366462,0.0008483733,0.0008208182,0.00223181,0.001616719,0.004211027,0.00385664,0.001533016,0.0112803],"category_scores_gemma":[0.01104096,0.001204256,0.002515259,0.001809099,0.004213667,0.006216612,0.00434961,0.003021158,0.003222392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001373245,"about_ca_system_score_gemma":0.0029841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001668951,"about_ca_topic_score_gemma":0.002290256,"domain_scores_codex":[0.9967787,0.0008645807,0.0003079205,0.0004623109,0.001341061,0.0002455626],"domain_scores_gemma":[0.992446,0.004471418,0.000275137,0.001644567,0.001013507,0.0001493223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000178448,0.000153156,0.000500457,0.0003433537,0.00005224309,0.0003254071,0.0003315341,0.0304379,0.0112491,0.7861324,0.007967659,0.1623284],"study_design_scores_gemma":[0.00005842144,0.00006860671,0.00007416682,0.00007966673,0.00007837942,0.0002424672,0.00008509758,0.2624685,0.02407845,0.6884122,0.0243002,0.00005379787],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008809875,0.00004187163,0.9958033,0.0001608734,0.00004276427,0.00006442535,0.00007053204,0.001138411,0.001796764],"genre_scores_gemma":[0.05839211,0.0001880756,0.9357331,0.0003280804,0.0001154819,0.0003041209,0.0004463887,0.0005369344,0.003955622],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0112803,"threshold_uncertainty_score":0.03773636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1721325510304666,"score_gpt":0.3455552282790685,"score_spread":0.1734226772486019,"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."}}