{"id":"W2912712767","doi":"","title":"Human-Agent Teaming as a Common Problem for Goal Reasoning.","year":2018,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Multi-agent system; Human–computer interaction; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.00106959,0.0002202196,0.0002000218,0.0001983753,0.0007829628,0.0004257555,0.0009507237,0.0001225697,0.0001504525],"category_scores_gemma":[0.0003667698,0.000220054,0.00008543743,0.0003655958,0.0001644534,0.0003256911,0.0001246214,0.0002589218,0.0005773145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001267074,"about_ca_system_score_gemma":0.0003836781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001119416,"about_ca_topic_score_gemma":0.000120935,"domain_scores_codex":[0.9977211,0.00009179061,0.0004774147,0.0006090671,0.0006794859,0.0004211352],"domain_scores_gemma":[0.9980239,0.0003333807,0.0002153593,0.000307945,0.0009874749,0.0001319667],"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":[0.00003009792,0.00008502191,0.00004701373,0.00001016593,0.00001181031,0.000002553026,0.0008032754,0.0004896568,0.001775047,0.9208908,0.0009875454,0.07486698],"study_design_scores_gemma":[0.00006259668,0.0009596093,0.0001696019,0.0002272105,0.000006572455,0.00001075914,0.0001300157,0.3486439,0.0368933,0.6086863,0.003801591,0.0004086137],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01157792,0.00002728238,0.9352123,0.002864934,0.0005121892,0.0005776012,0.00002341836,0.0003079833,0.0488964],"genre_scores_gemma":[0.9563202,0.000001696962,0.04163336,0.0008665484,0.0003515786,0.00008917753,0.00002097269,0.00001361222,0.0007029053],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9447422,"threshold_uncertainty_score":0.8973541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.111597563471133,"score_gpt":0.3768966286957244,"score_spread":0.2652990652245913,"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."}}