{"id":"W2366410293","doi":"","title":"Development of talking and mobile robot","year":2001,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Mobile robot; Robot; Engineering; China; Path (computing); Electrical engineering; Telecommunications; Computer science; Geography; Artificial intelligence; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003782322,0.0006568431,0.0004655254,0.0005681417,0.0007137242,0.0005267705,0.001327711,0.0008708959,0.005666428],"category_scores_gemma":[0.0005072523,0.0004446249,0.000602649,0.0002776794,0.0004047555,0.00127742,0.001004103,0.0008988822,0.003785786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002512086,"about_ca_system_score_gemma":0.0008390549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001334597,"about_ca_topic_score_gemma":0.0009548586,"domain_scores_codex":[0.9996527,0.00003681625,0.00001833747,0.00009804952,0.000151025,0.00004307997],"domain_scores_gemma":[0.999775,0.00002276694,0.0000121103,0.00002066247,0.0001194098,0.00004995878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001153557,0.0001679651,0.001442407,0.0009345584,0.0000615753,0.0006219478,0.0007946296,0.01181765,0.1185129,0.04299812,0.01934898,0.8031839],"study_design_scores_gemma":[0.0001264925,0.002703908,0.004200875,0.0003022271,0.0001963805,0.005465551,0.0007521826,0.1741714,0.201427,0.01174454,0.5984689,0.0004404892],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01322429,0.00137285,0.9537077,0.0003029775,0.0004878218,0.0003444437,0.00013518,0.004735905,0.02568878],"genre_scores_gemma":[0.1098318,0.001728676,0.8452809,0.0004606594,0.0001334104,0.000694224,0.0006467542,0.0003378963,0.04088569],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005666428,"threshold_uncertainty_score":0.01895612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02080759345184531,"score_gpt":0.2565232409120847,"score_spread":0.2357156474602394,"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."}}