{"id":"W2100655974","doi":"10.1007/978-3-540-85097-7_29","title":"The Robot Cleans Up","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Eulerian path; Enhanced Data Rates for GSM Evolution; Robot; Weighting; Property (philosophy); Graph; Artificial intelligence; Theoretical computer science; Mathematics; Lagrangian; Physics","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":[0.0004240697,0.0008852856,0.0007002061,0.0006354029,0.001875341,0.002453445,0.00100261,0.00189698,0.04036276],"category_scores_gemma":[0.00118919,0.0005344689,0.0008120064,0.0003074155,0.003852437,0.00416188,0.003142395,0.003277111,0.02379533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005091351,"about_ca_system_score_gemma":0.001135914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001550645,"about_ca_topic_score_gemma":0.001239122,"domain_scores_codex":[0.9996083,0.00005977084,0.000008942992,0.0001060584,0.0001474358,0.00006949168],"domain_scores_gemma":[0.9996636,0.00006102737,0.00001826592,0.0001248286,0.00006670361,0.00006562809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002256136,0.0001009051,0.0005130981,0.0003462092,0.00006054364,0.0005488866,0.00149009,0.00414636,0.02675641,0.5783152,0.1472659,0.2402307],"study_design_scores_gemma":[0.00002671657,0.0002250098,0.0005093949,0.0001393159,0.00003017272,0.0005251921,0.0007779914,0.004728956,0.008585434,0.1184999,0.865881,0.00007094963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02058106,0.003995913,0.2903992,0.01951113,0.006917065,0.0001526315,0.0003757179,0.007170333,0.6508969],"genre_scores_gemma":[0.2056806,0.00324138,0.08206431,0.006074742,0.001099995,0.0002011149,0.0004526041,0.001962723,0.6992224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04036276,"threshold_uncertainty_score":0.1350268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0202242425765905,"score_gpt":0.2330979798010388,"score_spread":0.2128737372244483,"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."}}