{"id":"W2051897947","doi":"10.1109/robot.2010.5509639","title":"Blinkered LOST: Restricting sensor field of view can improve scalability in emergent multi-robot trail following","year":2010,"lang":"en","type":"article","venue":"","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scalability; Computer science; Robot; Field (mathematics); Artificial intelligence; Real-time computing; Mathematics; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002704019,0.0001608871,0.0002666612,0.00008314489,0.0000264976,0.0000148096,0.000169255,0.0001420203,0.0005751955],"category_scores_gemma":[0.0003057706,0.0001466402,0.000127982,0.0002405881,0.00001303435,0.00006739679,0.00003643405,0.0004110366,0.00001506007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002593342,"about_ca_system_score_gemma":0.00002114086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001028244,"about_ca_topic_score_gemma":0.004372634,"domain_scores_codex":[0.9988159,0.00002171912,0.0004978972,0.0002326717,0.000142885,0.0002889604],"domain_scores_gemma":[0.9993755,0.0001053635,0.00003704449,0.0003540165,0.0000384877,0.00008955527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001331368,0.0002106353,0.02785325,0.000472603,0.0000843849,0.00003298893,0.001320685,0.02676554,0.7667603,0.0001665493,0.0001707733,0.176149],"study_design_scores_gemma":[0.0006813974,0.00009333507,0.01954781,0.0001437107,0.00002984337,0.000004764945,0.0004031534,0.275417,0.7023326,0.00009035831,0.000636415,0.0006196899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769507,0.0001034528,0.02032842,0.0001426948,0.0009208674,0.0003010404,0.000009821098,0.00009067843,0.001152315],"genre_scores_gemma":[0.9877308,0.00003021494,0.01197409,0.0000336114,0.0000427325,0.0000105766,0.000003741621,0.0000218645,0.0001523721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2486514,"threshold_uncertainty_score":0.6297987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02191923982801903,"score_gpt":0.2748264188361415,"score_spread":0.2529071790081225,"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."}}