{"id":"W1550040990","doi":"10.1007/978-3-642-05031-2_4","title":"Implementing MSC Tests with Quiescence Observation","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Asynchronous communication; Test (biology); Chart; Fault detection and isolation; Sequence (biology); Distributed computing; Fault (geology); Test case; Class (philosophy); Reliability engineering; Real-time computing; Embedded system; Programming language; Artificial intelligence; Computer network; Machine learning; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001225888,0.0005402119,0.0004441507,0.0006629415,0.0004135407,0.0007373858,0.003022829,0.000213798,0.000005668549],"category_scores_gemma":[0.0002378573,0.0004610693,0.0000736264,0.0008791779,0.0003828079,0.0007842992,0.001012713,0.0006907822,0.00001387647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002713197,"about_ca_system_score_gemma":0.0005343001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005561455,"about_ca_topic_score_gemma":0.00008575537,"domain_scores_codex":[0.9959379,0.00002626207,0.0004935771,0.001526339,0.001081996,0.0009338527],"domain_scores_gemma":[0.9969255,0.0006295548,0.0004004809,0.001530101,0.00037511,0.0001392372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000002762671,0.00001766828,0.001647097,0.00002303889,0.000004302656,0.00007132951,0.0002957274,0.001430497,0.00006137865,0.006036311,0.00008723544,0.9903226],"study_design_scores_gemma":[0.0003229404,0.0007393829,0.004015154,0.001999004,0.00001454317,0.0002601515,6.839824e-8,0.2508256,0.001819866,0.7359549,0.002560412,0.001487886],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001490284,0.0001762289,0.9929453,0.0007238773,0.0003199936,0.0003399534,0.000001575765,0.003745251,0.001598865],"genre_scores_gemma":[0.09658715,0.00001344723,0.9011765,0.001713495,0.0002443806,0.00000934766,0.000005043732,0.00003054595,0.0002200773],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9888347,"threshold_uncertainty_score":0.9997841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02877733741771017,"score_gpt":0.2694788400972328,"score_spread":0.2407015026795227,"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."}}