{"id":"W2703543743","doi":"","title":"Towards Tractable Inference for Resource-Bounded Agents","year":2015,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Inference; sort; Commonsense reasoning; Epistemic modal logic; Commonsense knowledge; Semantics (computer science); Non-monotonic logic; Artificial intelligence; Common sense; Rule of inference; Epistemology; Theoretical computer science; Description logic; Cognitive science; Knowledge representation and reasoning; Programming language; Multimodal logic; Psychology; Philosophy; Information retrieval","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007640167,0.0008823377,0.00138049,0.002059043,0.002119269,0.005039242,0.003505089,0.00273768,0.005345666],"category_scores_gemma":[0.03224565,0.00113955,0.004324863,0.00143847,0.004330493,0.01064553,0.007727157,0.005933417,0.000931053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004529371,"about_ca_system_score_gemma":0.002905631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0084935,"about_ca_topic_score_gemma":0.01204832,"domain_scores_codex":[0.9946102,0.002340508,0.0003466581,0.0009379829,0.001374831,0.0003898135],"domain_scores_gemma":[0.9783418,0.01685925,0.0007064693,0.002261286,0.001320844,0.0005104595],"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":[0.00003291472,0.00002956028,0.0002037316,0.0000874716,0.00004563277,0.0001946529,0.0003863446,0.0301447,0.0004743231,0.9592614,0.001445164,0.007694029],"study_design_scores_gemma":[0.00001395913,0.000005333573,0.00002807257,0.00001441887,0.00001871888,0.00002445975,0.00005255757,0.1218489,0.0003254505,0.8753321,0.002327107,0.000009077665],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01228064,0.0003123244,0.972283,0.00278556,0.000075606,0.00007340142,0.0001806991,0.0007073815,0.01130138],"genre_scores_gemma":[0.4149593,0.0006461908,0.5719245,0.00118646,0.0003421273,0.0003627395,0.0006902078,0.0003608391,0.009527587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0084935,"threshold_uncertainty_score":0.04040557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2847474463153415,"score_gpt":0.3935910568604578,"score_spread":0.1088436105451163,"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."}}