{"id":"W6987868162","doi":"","title":"Unsupervised learning for mobile robot terrain classification","year":2010,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Terrain; Mobile robot; Cluster analysis; Robot; Identification (biology); Unsupervised learning; Modality (human–computer interaction); Tactile sensor","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":[0.0009059695,0.0006997975,0.0009019364,0.000817703,0.0005821472,0.0008638536,0.00170314,0.001299963,0.002262301],"category_scores_gemma":[0.003815095,0.0004136378,0.0009040301,0.0009627509,0.0008721569,0.001166217,0.001133007,0.00145556,0.0009969011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001043494,"about_ca_system_score_gemma":0.0008467428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003799753,"about_ca_topic_score_gemma":0.003957807,"domain_scores_codex":[0.9994556,0.0001393635,0.00003389394,0.0001947324,0.0001233474,0.00005317217],"domain_scores_gemma":[0.9982656,0.0009377151,0.0001886316,0.0002818565,0.0002825128,0.00004379946],"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":[0.0001076948,0.0001250722,0.001926212,0.0002095326,0.0001022459,0.00009209465,0.0001106247,0.6672719,0.003520409,0.0214959,0.005152605,0.2998857],"study_design_scores_gemma":[0.000004252954,0.00001369869,0.0001872463,0.000006558439,0.000003567472,0.00001158183,0.00001078893,0.985454,0.000578319,0.01272131,0.00100366,0.000005033855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01000527,0.0005332328,0.9862303,0.0003742792,0.00006826883,0.00007126647,0.0001662946,0.0009551152,0.001596018],"genre_scores_gemma":[0.4946985,0.0007199423,0.4943152,0.0004000751,0.0003431269,0.0005836968,0.001439538,0.0002998011,0.007200048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003799753,"threshold_uncertainty_score":0.007571161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003119858208277862,"score_gpt":0.140896305675688,"score_spread":0.1377764474674101,"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."}}