{"id":"W4238854784","doi":"10.1007/978-3-642-44949-9","title":"Multi-disciplinary Trends in Artificial Intelligence","year":2013,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University; University of Winnipeg","funders":"Indian Institute of Technology Indore; University of Hyderabad; Jawaharlal Nehru Technological University Hyderabad; Southeast University; Yeungnam University; Technische Universität Clausthal; Indian Institute of Technology Delhi; King Mongkut's Institute of Technology Ladkrabang; University of Crete; Universität Trier; Commonwealth Scientific and Industrial Research Organisation; Technische Universität Darmstadt; Purdue University; Centre National de la Recherche Scientifique; Thammasat University; Indian Institute of Science; Université du Luxembourg","keywords":"Discipline; Computer science; Artificial intelligence; Social science; Sociology","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":[0.002023385,0.0007560347,0.000727098,0.003342275,0.0009541969,0.007337056,0.001131432,0.001521495,0.01486589],"category_scores_gemma":[0.003365478,0.0003770992,0.000551493,0.007070973,0.003037703,0.00929746,0.003331559,0.0037849,0.004587553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001984963,"about_ca_system_score_gemma":0.002542149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004550146,"about_ca_topic_score_gemma":0.001447391,"domain_scores_codex":[0.9987049,0.0002944348,0.0001144261,0.000150163,0.0006455503,0.00009058238],"domain_scores_gemma":[0.9969475,0.001478045,0.0001927168,0.0003296174,0.0006088915,0.0004432696],"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":[0.00003231085,0.00009288568,0.0005566228,0.001412635,0.00003559743,0.00008944901,0.0008136507,0.0006020464,0.0007384599,0.4808293,0.09688542,0.4179116],"study_design_scores_gemma":[0.000008156528,0.00003521045,0.001209293,0.0008126167,0.00001369823,0.0003577277,0.0005629663,0.001140947,0.0001993937,0.2605733,0.7350748,0.00001180872],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00449082,0.5613049,0.0174481,0.03363584,0.009164242,0.00004198838,0.00009994714,0.0001872706,0.3736268],"genre_scores_gemma":[0.1225339,0.5745775,0.03585161,0.01106679,0.02133812,0.000219172,0.0004480114,0.0003180357,0.2336469],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01486589,"threshold_uncertainty_score":0.04973143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0446468636590377,"score_gpt":0.2975143364681765,"score_spread":0.2528674728091388,"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."}}