{"id":"W3169794909","doi":"10.1109/icstw52544.2021.00040","title":"Test Sequence Generation with Cayley Graphs","year":2021,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Test suite; Computer science; Sequence (biology); Graph; Theoretical computer science; Set (abstract data type); Metric (unit); Finite-state machine; Algorithm; Test case; Programming language; Engineering; Machine learning","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":[0.00009743497,0.00006872043,0.00006081363,0.00003465503,0.00008186561,0.0001479852,0.0002316551,0.00002438842,0.000009979019],"category_scores_gemma":[0.0001860265,0.00005319668,0.00001592963,0.0004009301,0.0000215505,0.0002056701,0.00007245882,0.00003999352,0.0000137404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001427509,"about_ca_system_score_gemma":0.0001020417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004459602,"about_ca_topic_score_gemma":0.00003022102,"domain_scores_codex":[0.9993708,0.00001974163,0.0000768078,0.0002649924,0.0001446299,0.000123055],"domain_scores_gemma":[0.9992107,0.0001232842,0.00002482963,0.0004488482,0.0001494614,0.00004288408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000003042433,0.0004228117,0.1743332,0.00004160699,0.00003795015,0.001540142,0.001076827,0.0002336447,0.1390218,0.2821174,0.1568447,0.2443268],"study_design_scores_gemma":[0.000454781,0.000489004,0.00511267,0.0001210813,0.00001411175,0.002333486,0.00001050735,0.2692583,0.5855557,0.1331286,0.002578152,0.0009435796],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01184841,0.00004870073,0.9741229,0.0007619624,0.00006596388,0.00004071196,5.894932e-7,0.00835518,0.004755531],"genre_scores_gemma":[0.5033057,0.000003393714,0.4957708,0.0005496798,0.00001678803,0.000006765826,0.000002363151,0.000003185343,0.0003414032],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4914573,"threshold_uncertainty_score":0.2169297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04702509873227484,"score_gpt":0.2644447797892314,"score_spread":0.2174196810569565,"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."}}