{"id":"W2936740280","doi":"10.1002/cpe.5205","title":"Model checking ontology‐driven reasoning agents using strategy and abstraction","year":2019,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Abstraction; Model checking; Linear temporal logic; Ontology; Programming language; Temporal logic; Encoding (memory); Exploit; Theoretical computer science; 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":[0.0001687752,0.0001239409,0.0001483742,0.00005499645,0.0002169415,0.0002704781,0.000116753,0.00006674953,0.000002778723],"category_scores_gemma":[0.0001050993,0.0001205553,0.00001328843,0.000101787,0.0000844612,0.002357791,0.0001155369,0.000133616,0.000003702511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001316676,"about_ca_system_score_gemma":0.0000526402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001042473,"about_ca_topic_score_gemma":0.000004895002,"domain_scores_codex":[0.9990305,0.00005862208,0.0001940686,0.000404887,0.0001329802,0.0001789797],"domain_scores_gemma":[0.9993449,0.0002044555,0.0001822245,0.0001197721,0.00008165285,0.00006703906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001168827,0.0002220032,0.06838013,0.0002540033,0.00009458902,0.00008268138,0.09047747,0.04469404,0.008401649,0.1713219,0.00007352637,0.6158811],"study_design_scores_gemma":[0.0002938944,0.00006883458,0.01035708,0.00004563823,0.00001206972,0.0001873135,0.004360609,0.9830197,0.00008319602,0.001266192,0.000142817,0.0001626382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7543887,0.0008966345,0.2433136,0.0001546265,0.0002049668,0.00009861679,2.926782e-7,0.00006484626,0.0008776055],"genre_scores_gemma":[0.9754693,0.0002983997,0.02397601,0.0002130683,0.00001562572,0.000004999428,8.605723e-7,0.000004373883,0.00001739364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9383257,"threshold_uncertainty_score":0.4916104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07800741567634234,"score_gpt":0.3675260329587255,"score_spread":0.2895186172823832,"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."}}