{"id":"W2293074099","doi":"","title":"What a Sunflower Can Teach a Robot? - Efficient Robot Queuing by Reverse Phyllotaxis.","year":2010,"lang":"en","type":"article","venue":"Artificial Life","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Robot; Computer science; Controller (irrigation); Queue; Queueing theory; Phyllotaxis; Simple (philosophy); Control theory (sociology); Interference (communication); Mathematical optimization; Distributed computing; Artificial intelligence; Mathematics; Control (management); Computer network","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":[0.0008048378,0.000223636,0.0002717565,0.0001044953,0.0003539302,0.0009292198,0.000675817,0.0001568218,0.00008926814],"category_scores_gemma":[0.0001435659,0.0002060743,0.0001450567,0.0003935299,0.00006627328,0.0004947056,0.0001740824,0.0004678328,0.0002332636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000049204,"about_ca_system_score_gemma":0.0001069756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008239934,"about_ca_topic_score_gemma":0.00144653,"domain_scores_codex":[0.9978461,0.0001363857,0.0004916358,0.0006014738,0.0003952954,0.0005291692],"domain_scores_gemma":[0.9985733,0.00009804114,0.0001601168,0.0007344364,0.0001430859,0.0002910205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001273202,0.001503214,0.0008824356,0.00007088645,0.000201302,0.0001370284,0.02100036,0.04771145,0.3773126,0.2102519,0.2586965,0.08210497],"study_design_scores_gemma":[0.0006191285,0.0002781729,0.0003550912,0.0002015964,0.00002589305,0.00008531773,0.001718676,0.7536244,0.01793684,0.0009550261,0.222849,0.001350842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.61988,0.0002728011,0.3301288,0.01308452,0.03292523,0.0007847674,0.000009359981,0.0007258535,0.002188613],"genre_scores_gemma":[0.9947909,0.000004772656,0.001368721,0.001788762,0.0009346771,0.00003419051,0.000005229921,0.00002219498,0.001050615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7059129,"threshold_uncertainty_score":0.8960488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01271517958026363,"score_gpt":0.2342933924876934,"score_spread":0.2215782129074298,"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."}}