{"id":"W2620408778","doi":"10.1002/rob.21722","title":"Adaptive continuous‐space informative path planning for online environmental monitoring","year":2017,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":139,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Motion planning; Computer science; Path (computing); Real-time computing; Mobile robot; Field (mathematics); Parameterized complexity; Planner; Focus (optics); Scheme (mathematics); Robot; Distributed computing; Computation; Artificial intelligence; Algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004114641,0.0007638377,0.0005131133,0.0005122296,0.0002970978,0.0004694302,0.0009670135,0.0006625673,0.001010586],"category_scores_gemma":[0.001188915,0.0004152123,0.0005237719,0.0004949109,0.000569072,0.0005172034,0.0007675391,0.000779404,0.0001384952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000618015,"about_ca_system_score_gemma":0.0008885395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006864558,"about_ca_topic_score_gemma":0.005801319,"domain_scores_codex":[0.9997466,0.00007001,0.00000874137,0.0000689553,0.0000705741,0.00003512279],"domain_scores_gemma":[0.999495,0.0003004254,0.00006310827,0.00004516084,0.00006659386,0.00002955983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002948008,0.00001694729,0.0002278217,0.00002119788,0.00001148589,0.00003209232,0.00002710458,0.9797502,0.001458992,0.001391373,0.0002642889,0.01676904],"study_design_scores_gemma":[0.000002660527,0.00000848433,0.00005028379,0.000001188194,0.000001473107,0.000004237117,0.000003164327,0.9989595,0.0002154228,0.0006283578,0.000123845,0.000001425821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03125373,0.000137695,0.9667603,0.00009448209,0.00001630137,0.00002488667,0.00004670027,0.0005690717,0.00109698],"genre_scores_gemma":[0.8259678,0.00009861716,0.172485,0.00004314453,0.00001412027,0.0001026967,0.0001289492,0.00006877106,0.001090881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006864558,"threshold_uncertainty_score":0.01364917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04061611656066819,"score_gpt":0.3027307588796727,"score_spread":0.2621146423190045,"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."}}