{"id":"W4400972601","doi":"10.2316/j.2024.206-1059","title":"VISION-BASED ROBOT INDOOR-POSITIONING AND NAVIGATION METHOD RESEARCH, 1-9.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer vision; Computer science; Artificial intelligence; Mobile robot navigation; Robot; Human–computer interaction; Mobile robot; Robot control","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001957561,0.00008767062,0.0001194172,0.0005426412,0.0001121139,0.0009454695,0.0003228051,0.00006654502,0.000002198381],"category_scores_gemma":[0.0001459357,0.00007693285,0.00004079529,0.0002638126,0.00004726314,0.0009153864,0.0000967427,0.0003279952,0.000004616111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009572979,"about_ca_system_score_gemma":0.0001401386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001020545,"about_ca_topic_score_gemma":2.149693e-7,"domain_scores_codex":[0.9982941,0.0001694459,0.0003720269,0.0001829213,0.0008550104,0.0001265507],"domain_scores_gemma":[0.9984041,0.0005857592,0.0001563401,0.00009039104,0.0006807671,0.00008258427],"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":[0.00001910888,0.00008795784,0.0006034435,0.00009199971,0.0001718667,0.0005081474,0.001736345,0.4813739,0.007494322,0.08609348,0.0008744088,0.420945],"study_design_scores_gemma":[0.0002387577,0.0001352533,0.003911525,0.0007234745,0.000009834503,0.000517594,0.00002539287,0.9821503,0.0008304122,0.01118022,0.0001996857,0.00007751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004841206,0.0005706542,0.9855471,0.007781604,0.001059343,0.00005748342,0.000002003175,0.00005478457,0.00008584607],"genre_scores_gemma":[0.43769,0.00002941614,0.5620058,0.00007682196,0.0001677537,0.000001180917,0.000005389141,0.000006175027,0.00001745654],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5007764,"threshold_uncertainty_score":0.9117184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02824025932894523,"score_gpt":0.3889500768446982,"score_spread":0.3607098175157529,"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."}}