{"id":"W2087027772","doi":"10.1177/0278364913478897","title":"The Canadian planetary emulation terrain 3D mapping dataset","year":2013,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Space Agency; Institute for Christian Studies; University of Toronto","funders":"","keywords":"Terrain; Emulation; Scripting language; Computer science; Robotics; Artificial intelligence; Field (mathematics); Panning (audio); Robot; Computer vision; Computer graphics (images); Engineering; Cartography; Geography; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004722992,0.00286595,0.001244453,0.004448857,0.002540463,0.00178751,0.004338796,0.00149077,0.01303713],"category_scores_gemma":[0.002403646,0.0006507359,0.00107325,0.01027961,0.0009512777,0.001041583,0.002139185,0.001913488,0.01221266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006090082,"about_ca_system_score_gemma":0.01221475,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8645209,"about_ca_topic_score_gemma":0.9556495,"domain_scores_codex":[0.9987631,0.0000553291,0.00003932515,0.0002276802,0.0006797451,0.000234863],"domain_scores_gemma":[0.9985628,0.00009011742,0.0000458884,0.000305105,0.0008368328,0.0001594041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001715373,0.0001072197,0.004830333,0.0004373971,0.0001098473,0.0002792398,0.0001242121,0.005264785,0.001450137,0.001412176,0.9504401,0.03537312],"study_design_scores_gemma":[0.0001874664,0.00003431684,0.02793966,0.0002747168,0.00007466107,0.000341569,0.0006305918,0.01435405,0.004113954,0.001653248,0.9502368,0.0001589145],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005419683,0.0004476351,0.001582129,0.000221748,0.00006441183,0.0001308487,0.9830836,0.002978545,0.006071418],"genre_scores_gemma":[0.007213993,0.0002005914,0.003942899,0.00004516205,0.000007080978,0.00008189186,0.9871416,0.0001863895,0.001180459],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1354791,"threshold_uncertainty_score":0.2725539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05919476706959579,"score_gpt":0.311463517561405,"score_spread":0.2522687504918092,"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."}}