{"id":"W4403004482","doi":"10.23977/jeis.2024.090310","title":"A SLAM method based on deep learning","year":2024,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Deep learning; Computer science; Computer vision","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":[0.0008451163,0.00004860516,0.00006274963,0.0003600517,0.00007528932,0.0002583361,0.00006985722,0.00002137498,0.000007288598],"category_scores_gemma":[0.00008386001,0.00003819745,0.00002403649,0.0004732229,0.00002049141,0.001568194,0.000004166774,0.0002018846,0.000004312958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008394005,"about_ca_system_score_gemma":0.0001045353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.455839e-7,"about_ca_topic_score_gemma":1.916113e-7,"domain_scores_codex":[0.9993429,0.000008751343,0.0002189914,0.00003251585,0.000270996,0.0001258715],"domain_scores_gemma":[0.9996925,0.00004937223,0.00004561734,0.00003687257,0.0001261567,0.0000494589],"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":[0.000002691009,0.00000134906,0.000006324779,0.00001808399,0.000002035375,5.130627e-7,0.0001442659,0.9410453,0.0009092744,0.01386846,0.00003511546,0.04396662],"study_design_scores_gemma":[0.00007751721,0.0001491196,0.00009121022,0.00003100607,0.000004327732,0.00001734988,0.00002867571,0.9679413,0.001768611,0.0001826884,0.02966344,0.00004469725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01310208,0.0004531577,0.9817994,0.0001666033,0.0002096358,0.00002888749,2.403758e-7,0.0000288925,0.004211159],"genre_scores_gemma":[0.9944667,0.0004521216,0.004919778,0.0001239272,0.00002701442,3.209475e-7,7.898011e-7,0.000003634626,0.000005724412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9813646,"threshold_uncertainty_score":0.2491141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004440479754016132,"score_gpt":0.2396434101739845,"score_spread":0.2352029304199684,"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."}}