{"id":"W2153412140","doi":"10.1109/robot.1991.132015","title":"Optical range image acquisition for the navigation of a mobile robot","year":2002,"lang":"en","type":"article","venue":"","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Mobile robot; Computer vision; Computer science; Range (aeronautics); Artificial intelligence; Robot; Real-time computing; Engineering; Aerospace engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00005065657,0.00003895562,0.00004502008,0.0000110661,0.0000390254,0.00001581872,0.00006289451,0.00002392403,0.000100161],"category_scores_gemma":[0.000003159479,0.00002807771,0.00002881837,0.00006443675,0.00002455777,0.00006485706,0.000006328415,0.00003068329,0.000009587798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008897528,"about_ca_system_score_gemma":8.518901e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001759576,"about_ca_topic_score_gemma":1.473955e-7,"domain_scores_codex":[0.9997594,0.000001398322,0.00008988894,0.00004575943,0.0000397558,0.00006373827],"domain_scores_gemma":[0.9997984,0.0000399435,0.00001104471,0.0001024003,0.00003811157,0.00001016178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001009906,0.0001911935,0.00002081423,0.0005275277,0.00004486005,5.742885e-7,0.000719333,0.009554042,0.6127757,0.02873746,0.03982165,0.3075967],"study_design_scores_gemma":[0.000145158,0.00002660057,0.00005839341,0.00001900802,0.00001955666,0.000003160448,0.00003932717,0.8015094,0.1934859,0.001745237,0.002874175,0.00007407054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002765956,0.0002665304,0.9917035,0.0001806647,0.00001454976,0.0002991487,0.000005300642,0.0002348091,0.004529509],"genre_scores_gemma":[0.8798524,0.00003074284,0.1195159,0.00002080879,0.00003150165,0.0004036412,0.000005772679,0.000009849459,0.0001294517],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8770864,"threshold_uncertainty_score":0.1144976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01394095968105917,"score_gpt":0.2558145465049745,"score_spread":0.2418735868239154,"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."}}