{"id":"W1589644135","doi":"10.1007/978-3-642-38457-8_16","title":"Boundary Set Based Existence Recognition and Construction of Hypertree Agent Organization","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Hyperbolic tree; Set (abstract data type); Constraint (computer-aided design); Probabilistic logic; Tree (set theory); Boundary (topology); Multi-agent system; Theoretical computer science; Inference; Artificial intelligence; Mathematics; Programming language","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":[0.0002977541,0.0002681921,0.0002856298,0.0005978823,0.0001783344,0.0003214084,0.0005062748,0.000207639,0.0001386901],"category_scores_gemma":[0.0001118304,0.0002673523,0.00004061301,0.000557604,0.0007685084,0.0006905067,0.0002468301,0.0002645933,0.00002742003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001470206,"about_ca_system_score_gemma":0.0004418645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002073732,"about_ca_topic_score_gemma":0.00002276512,"domain_scores_codex":[0.9980535,0.00003406407,0.0004221577,0.000780066,0.0004904734,0.0002197629],"domain_scores_gemma":[0.9983376,0.0001829703,0.0003478618,0.0004967963,0.0005367214,0.00009800321],"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":[0.000002396634,0.0000100375,0.0003400478,0.00004624894,0.000005230524,0.000004900724,0.0002713232,0.003315646,0.0002735692,0.00331202,0.000008608727,0.9924099],"study_design_scores_gemma":[0.0006304767,0.0002192349,0.003239586,0.000641434,0.0000230465,0.000234571,0.000001451469,0.8653041,0.005235631,0.1232426,0.0004010487,0.0008267954],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001242982,0.0000799089,0.9961092,0.0004797096,0.0008294307,0.0003163617,0.00001136932,0.00009604865,0.0008349578],"genre_scores_gemma":[0.1043944,0.0001003111,0.8945795,0.000668455,0.0001015893,0.000005195867,0.00005064294,0.00002290165,0.00007702586],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9915832,"threshold_uncertainty_score":0.9999779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02377325258255158,"score_gpt":0.2171652799582494,"score_spread":0.1933920273756978,"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."}}