{"id":"W2070368455","doi":"10.1016/s0004-3702(02)00365-x","title":"Knowledge, action, and the frame problem","year":2003,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":276,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Action (physics); Computer science; GRASP; Frame (networking); Frame problem; Knowledge representation and reasoning; Artificial intelligence; Object (grammar); Affect (linguistics); Successor cardinal; Cognitive science; Knowledge management; Mathematics; Programming language; Psychology; Communication","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":[0.004245333,0.0007915858,0.001159404,0.002084927,0.003180589,0.006907688,0.002005928,0.005278386,0.0101049],"category_scores_gemma":[0.01165676,0.0006521878,0.001323655,0.002357404,0.0116505,0.01884831,0.003024863,0.003380874,0.0009913457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003824291,"about_ca_system_score_gemma":0.00270457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01584084,"about_ca_topic_score_gemma":0.007767883,"domain_scores_codex":[0.9974963,0.001228845,0.0001664611,0.0004857369,0.0003444213,0.0002782784],"domain_scores_gemma":[0.9940948,0.004490598,0.0003419011,0.0004903695,0.0003324446,0.0002500222],"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":[0.00003596517,0.00001382789,0.00008867598,0.00003723035,0.000006890878,0.00004861175,0.0001971118,0.001142792,0.00004463359,0.9896231,0.001673339,0.007087992],"study_design_scores_gemma":[0.00001293378,0.000003418999,0.00003298731,0.00001624083,0.000005298657,0.00002048004,0.0001000612,0.001881953,0.00004035158,0.9941567,0.003724857,0.000004598406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07490284,0.02133378,0.5578963,0.07161082,0.001306863,0.0001767957,0.0009909999,0.0004869861,0.2712947],"genre_scores_gemma":[0.8484771,0.007530442,0.1157083,0.001839555,0.001004428,0.000272088,0.00101904,0.0001067512,0.02404237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01584084,"threshold_uncertainty_score":0.03380424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06070968582728412,"score_gpt":0.3073802869727568,"score_spread":0.2466706011454727,"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."}}