{"id":"W2794780478","doi":"10.5539/mas.v12n4p171","title":"A Simple and Inexpensive 3D Scanning of Remote Objects by Robot","year":2018,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Robot; Computer vision; Object (grammar); Obstacle; Mobile robot; Artificial intelligence; Controller (irrigation); Process (computing); Obstacle avoidance; Remote control; 3d scanning; Computer hardware; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001844992,0.0007182244,0.0006246813,0.0008696573,0.0003235324,0.0005860427,0.001043733,0.0008072197,0.008705889],"category_scores_gemma":[0.000365704,0.000530849,0.0006201846,0.000592793,0.0004344901,0.001011337,0.001062204,0.0004975811,0.003911915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001774591,"about_ca_system_score_gemma":0.0004132877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00102265,"about_ca_topic_score_gemma":0.001745379,"domain_scores_codex":[0.9993856,0.00003929496,0.0000178947,0.0001360836,0.0003792841,0.00004185077],"domain_scores_gemma":[0.9996899,0.00005333529,0.00003932563,0.0001336613,0.00006216124,0.00002158489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001578418,0.00009201716,0.001845446,0.0004488236,0.00003688852,0.0005113023,0.0002717887,0.004880484,0.6668789,0.003394285,0.005682445,0.3157998],"study_design_scores_gemma":[0.00009279804,0.001537051,0.01967569,0.0002177357,0.0001078047,0.009248158,0.0006061178,0.1077309,0.6648366,0.004020308,0.1915992,0.0003275721],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07634897,0.001382994,0.8939028,0.0002702598,0.0001996101,0.0002660028,0.0004421125,0.005448667,0.02173861],"genre_scores_gemma":[0.3418556,0.001321345,0.6355771,0.0001867769,0.00008502624,0.0002161097,0.0007102217,0.0002418387,0.01980594],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008705889,"threshold_uncertainty_score":0.02912408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009178885618858264,"score_gpt":0.2195481956870017,"score_spread":0.2103693100681434,"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."}}