{"id":"W2025270539","doi":"10.1016/j.artint.2010.04.005","title":"A semantic characterization of a useful fragment of the situation calculus with knowledge","year":2010,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Situation calculus; Correctness; Fragment (logic); Calculus (dental); Embedding; Determinacy; Mathematics; Computer science; Algebra over a field; Artificial intelligence; Algorithm; Pure mathematics","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":[0.0002794861,0.0001040409,0.0001461604,0.0000614695,0.0000902387,0.00003747828,0.0006263343,0.00005877891,0.00002583445],"category_scores_gemma":[0.0001058569,0.00006678567,0.00005790862,0.000571395,0.0001588577,0.0001995392,0.0001455862,0.0001313757,0.00003897657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001301038,"about_ca_system_score_gemma":0.0001210211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000482354,"about_ca_topic_score_gemma":0.000514823,"domain_scores_codex":[0.9990308,0.00005704384,0.0003182739,0.0002291123,0.000207547,0.0001572157],"domain_scores_gemma":[0.9988629,0.00007136408,0.000230923,0.0004990014,0.0002945035,0.00004136889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001765638,0.0003422824,0.002907355,0.00003985345,0.00001648901,0.000001116108,0.008992702,0.00005636629,0.5280662,0.3832191,0.00000612109,0.07633483],"study_design_scores_gemma":[0.00002771069,0.0001239275,0.0155047,0.00005567081,0.00001386795,0.000005907628,0.00007223616,0.07402309,0.904272,0.00556939,0.0002093879,0.0001221239],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5738916,0.000009251605,0.4248202,0.0001152377,0.0003803532,0.0001528877,0.000001093254,0.00002088222,0.0006085695],"genre_scores_gemma":[0.9987569,0.000004474223,0.001049007,0.00002100989,0.0000590612,0.00001047457,0.000001530182,0.000005647406,0.00009185125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4248654,"threshold_uncertainty_score":0.2723441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.023592062439281,"score_gpt":0.2558285231445378,"score_spread":0.2322364607052568,"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."}}