{"id":"W4393160970","doi":"10.1609/aaai.v38i18.30040","title":"Bayesian Inference with Complex Knowledge Graph Evidence","year":2024,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto","funders":"","keywords":"Inference; Computer science; Bayesian inference; Bayesian statistics; Graph; Bayesian probability; Artificial intelligence; Machine learning; Theoretical computer science","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007828045,0.0004636311,0.0004204013,0.0003299809,0.0003100669,0.00110341,0.00354614,0.0001480302,0.0001073361],"category_scores_gemma":[0.0003449719,0.0003087702,0.0001883622,0.002193369,0.0006159802,0.001215046,0.0005638934,0.000692373,0.0002519912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007641363,"about_ca_system_score_gemma":0.0004677413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005957262,"about_ca_topic_score_gemma":0.00003424761,"domain_scores_codex":[0.9967844,0.00004541215,0.0007271887,0.001065663,0.0007537542,0.0006236094],"domain_scores_gemma":[0.9974993,0.000426522,0.0002482023,0.0006275168,0.0009853602,0.0002130536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004097489,0.0001089146,0.0001029752,0.0001682808,0.00002996744,0.000002983834,0.001597263,0.0001303985,0.01528685,0.894476,0.0003342011,0.08772121],"study_design_scores_gemma":[0.0000282855,0.0005847203,0.0002014625,0.003579766,0.00003996335,0.00003164316,0.0002685001,0.5126175,0.1233684,0.3583857,0.0002792629,0.0006148188],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01524266,0.0004717328,0.9556038,0.006575305,0.0007072134,0.0005881824,0.000008168618,0.0006334793,0.02016948],"genre_scores_gemma":[0.989967,0.0001635224,0.009109896,0.000207804,0.00009559508,0.00005599875,5.562177e-7,0.00002788055,0.0003717497],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9747244,"threshold_uncertainty_score":0.9999365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1491436242663293,"score_gpt":0.344951512490777,"score_spread":0.1958078882244477,"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."}}