{"id":"W3138727095","doi":"","title":"On Multi-Robot Area Coverage","year":2013,"lang":"en","type":"book-chapter","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Robot; Task (project management); Path (computing); Point (geometry); Mobile robot; Human–computer interaction; Actuator; Artificial intelligence; Real-time computing; Motion planning; Computer vision; Computer network; Engineering; Systems engineering","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001268942,0.0004737479,0.0004269133,0.0002006336,0.00008845016,0.0002299448,0.001401061,0.0003718915,0.0009238019],"category_scores_gemma":[0.00003315819,0.0003986503,0.0001547892,0.00003351972,0.00004686507,0.0002097479,0.0003591632,0.0005326655,0.01237575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009909922,"about_ca_system_score_gemma":0.00008446518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002603422,"about_ca_topic_score_gemma":9.941987e-7,"domain_scores_codex":[0.9979535,0.00001559169,0.0003264109,0.0008162332,0.0005186751,0.0003695829],"domain_scores_gemma":[0.9979436,0.0002180212,0.0001955393,0.001357638,0.00009465465,0.0001905151],"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":[0.000002063379,0.0000517821,0.000002687919,0.00001952362,0.00008179112,0.0003333578,0.0001127079,0.004979785,0.00001166612,0.8758586,0.07476207,0.04378394],"study_design_scores_gemma":[0.001478188,0.0005969042,0.0002810585,0.0008859304,0.00004228557,0.0001679464,0.000002027403,0.7527845,0.00009881976,0.1016103,0.1392322,0.002819812],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[4.073394e-7,0.00004088342,0.5148373,0.0001346772,0.0006175039,0.0001705523,0.000004559522,0.000287413,0.4839067],"genre_scores_gemma":[0.00008800385,0.00001887276,0.2738433,0.0009946595,0.00008055881,0.000009159179,0.00001321109,0.00003642497,0.7249157],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7742483,"threshold_uncertainty_score":0.9999895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04605794693522053,"score_gpt":0.2451152167638179,"score_spread":0.1990572698285974,"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."}}