{"id":"W2802275843","doi":"10.1109/access.2018.2827305","title":"On Invoking Transitivity to Enhance the &lt;italic&gt;Pursuit&lt;/italic&gt;-Oriented Object Migration Automata","year":2018,"lang":"en","type":"article","venue":"IEEE Access","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transitive relation; Computer science; Theoretical computer science; Pairwise comparison; Automaton; Phenomenon; Markov chain; Transitive closure; Algorithm; Discrete mathematics; Combinatorics; Artificial intelligence; Mathematics; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009554334,0.0002558528,0.0002205046,0.0002035178,0.0005585997,0.001102541,0.00216,0.00009779516,0.00003999181],"category_scores_gemma":[0.0001713305,0.0001966965,0.00008541672,0.001456903,0.0001350571,0.001785893,0.00026644,0.0001908266,0.0002126637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000968685,"about_ca_system_score_gemma":0.0001226341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001168079,"about_ca_topic_score_gemma":0.001079185,"domain_scores_codex":[0.9972504,0.0002932457,0.0003560873,0.0007144328,0.0008520314,0.0005337694],"domain_scores_gemma":[0.9980114,0.0002244535,0.0001385929,0.001082793,0.0003551752,0.0001875913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004852351,0.002135492,0.001207449,0.0002543583,0.0003537603,0.0001244851,0.06006967,0.03662869,0.3040566,0.2163253,0.1402811,0.2380778],"study_design_scores_gemma":[0.001049616,0.001133532,0.006351601,0.0003026866,0.00002634467,0.00002507924,0.00006591687,0.7208917,0.22983,0.003335854,0.03586747,0.001120212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2777902,0.00002056619,0.7105249,0.004778136,0.001141737,0.0006771234,0.00001442137,0.0003914585,0.004661405],"genre_scores_gemma":[0.9927779,0.00001676286,0.003004427,0.003353929,0.0002512965,0.00009690581,0.00001075499,0.0000231,0.0004648586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7149878,"threshold_uncertainty_score":0.9999344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02383690043812528,"score_gpt":0.3278256711858171,"score_spread":0.3039887707476918,"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."}}