{"id":"W7124164380","doi":"10.65109/cehc2496","title":"On Ability to Autonomously Execute Agent Programs with Sensing","year":2004,"lang":"","type":"article","venue":"","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Process (computing); Field (mathematics); Software; Action (physics); Troubleshooting; Automation","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"],"consensus_categories":[],"category_scores_codex":[0.0009773502,0.0005443528,0.0004264339,0.0001643487,0.0006075627,0.0009582176,0.0007490505,0.0001599311,0.00004270645],"category_scores_gemma":[0.00005085103,0.0004435641,0.0001299127,0.001000262,0.000131813,0.0003607585,0.0002935577,0.0005052925,0.0005128809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004962442,"about_ca_system_score_gemma":0.0007956196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009272677,"about_ca_topic_score_gemma":0.0001816743,"domain_scores_codex":[0.9959728,0.0001456033,0.0005539358,0.001486031,0.0007070169,0.001134607],"domain_scores_gemma":[0.997374,0.0001461925,0.0001744299,0.001410842,0.0002116542,0.0006829094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002371937,0.0007361176,0.0008680816,0.0001501757,0.00008729221,0.0005401076,0.01818288,0.2893038,0.0002495892,0.02224345,0.0005371494,0.6668641],"study_design_scores_gemma":[0.01221194,0.05625427,0.008502585,0.01295985,0.0004062968,0.001293225,0.001653964,0.8066168,0.02434825,0.03899262,0.0255904,0.01116984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2474518,0.00004252516,0.7386873,0.005514414,0.0005058589,0.0009206878,0.000002335637,0.0004924423,0.006382595],"genre_scores_gemma":[0.7245227,0.000001213608,0.2725564,0.002144145,0.00007538926,0.000008243235,0.000003776959,0.00002526732,0.0006629137],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6556943,"threshold_uncertainty_score":0.9998016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02036998959071791,"score_gpt":0.2401023474403474,"score_spread":0.2197323578496295,"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."}}