{"id":"W4415968646","doi":"10.1109/iecon58223.2025.11221097","title":"A Dual Calibration Framework for Exploring Environments using Heterogeneous Robot Swarms","year":2025,"lang":"","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Robot; RSS; Field (mathematics); Calibration; Exploit; Information exchange; Bridge (graph theory); Heterogeneous network; Spatial analysis","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"],"consensus_categories":[],"category_scores_codex":[0.0001313679,0.0004028821,0.0003684816,0.0002230295,0.0003013839,0.0002176686,0.0001273799,0.0003480657,0.0001193178],"category_scores_gemma":[0.00008036361,0.0004660067,0.0001894705,0.0003238083,0.00004010262,0.000328095,0.00007046959,0.0002170522,0.00001106725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003417373,"about_ca_system_score_gemma":0.00004753018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003102556,"about_ca_topic_score_gemma":0.000005237276,"domain_scores_codex":[0.9979593,0.00004694788,0.000687641,0.0004999668,0.0002381506,0.0005680538],"domain_scores_gemma":[0.9991649,0.0001844259,0.00008348594,0.0004115351,0.00002602609,0.0001296574],"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":[0.00003556607,0.00007522749,0.0001271738,0.0002122196,0.0001783942,0.000005739922,0.0002199867,0.9711059,0.0135737,0.01237498,0.00003233076,0.002058829],"study_design_scores_gemma":[0.000473857,0.00006456492,0.0000328381,0.0002717503,0.0001523287,0.000002721674,0.0001176197,0.8948656,0.09991051,0.002799784,0.000920761,0.0003876155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03342132,0.0004404385,0.9627596,0.0001702827,0.002224539,0.0007608964,0.00001596873,0.00009770272,0.0001092108],"genre_scores_gemma":[0.8871712,0.0002827539,0.1114464,0.0002109679,0.0003215618,0.00007471092,0.00005084916,0.00009751212,0.0003440273],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8537499,"threshold_uncertainty_score":0.9997792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05843533839788272,"score_gpt":0.2681370633549291,"score_spread":0.2097017249570464,"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."}}