{"id":"W7109983441","doi":"10.4230/lipics.concur.2025.36","title":"Explainability is a Game for Probabilistic Bisimilarity Distances","year":2025,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Probabilistic logic; State (computer science); Markov chain; Markov process; Markov decision process; Exponential function; Upper and lower bounds; Sequential game","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004431743,0.0009324373,0.0009721123,0.001090442,0.001585462,0.002858193,0.001839126,0.003045836,0.00534479],"category_scores_gemma":[0.0270496,0.0007011817,0.001974487,0.0008496949,0.005271113,0.007865365,0.003349282,0.004828342,0.000439485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002999402,"about_ca_system_score_gemma":0.002136515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003140021,"about_ca_topic_score_gemma":0.002789797,"domain_scores_codex":[0.9948665,0.002313375,0.0003032541,0.001041754,0.0009692014,0.0005058869],"domain_scores_gemma":[0.9745219,0.02131388,0.0009654309,0.00172677,0.0008551165,0.0006169172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006969187,0.00004538095,0.0005607093,0.0000729347,0.00003369073,0.0001206706,0.0004751553,0.04573102,0.001450067,0.9411138,0.0006748568,0.009651844],"study_design_scores_gemma":[0.00002218708,0.00002819213,0.0001344249,0.00001517296,0.00002125246,0.00005555646,0.00007071633,0.1379114,0.0008638896,0.8592512,0.001602678,0.00002343338],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04907266,0.0001066743,0.9404729,0.002100226,0.00004283333,0.000166479,0.0001949022,0.0002976792,0.007545681],"genre_scores_gemma":[0.7212654,0.0002430874,0.2727266,0.0005695325,0.00007725961,0.0004440166,0.0002740835,0.0002033783,0.004196566],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00534479,"threshold_uncertainty_score":0.02343756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02050632036176338,"score_gpt":0.2980518053021301,"score_spread":0.2775454849403667,"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."}}