{"id":"W2110380922","doi":"10.1109/icra.2014.6906913","title":"Curiosity based exploration for learning terrain models","year":2014,"lang":"en","type":"article","venue":"","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Terrain; Perplexity; Discriminative model; Path (computing); Visualization; Plan (archaeology)","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":[0.0004444618,0.00007923358,0.00007989156,0.00005977245,0.0002188082,0.0001053958,0.0003885484,0.00003527564,0.000007613486],"category_scores_gemma":[0.0001422849,0.0000744345,0.00004355715,0.0001350888,0.0000113847,0.000507057,0.00006100694,0.0001059998,0.00003842861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001848904,"about_ca_system_score_gemma":0.00002099689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001220102,"about_ca_topic_score_gemma":0.00001217933,"domain_scores_codex":[0.9992377,0.00008594806,0.000122511,0.0002842562,0.0001181474,0.0001514764],"domain_scores_gemma":[0.999231,0.0002347138,0.00006034152,0.0003505039,0.0000683472,0.00005507809],"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":[0.000002773707,0.00003986698,0.0004743304,0.000009775755,0.000002531881,3.314902e-8,0.0004150926,0.5033538,0.001035269,0.4235332,0.0002681463,0.07086522],"study_design_scores_gemma":[0.0002241934,0.00004910154,0.000592954,0.000003220429,0.000001580683,2.076232e-7,0.000005216646,0.9583841,0.0005514819,0.0362252,0.003867605,0.00009516204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004146209,0.00000169198,0.9857109,0.005375429,0.00003968403,0.0002268742,3.238554e-7,0.0004761785,0.004022662],"genre_scores_gemma":[0.6545423,1.45042e-7,0.3447091,0.000443824,0.00003045989,0.0001025594,0.000007062968,0.000005661584,0.0001589457],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.650396,"threshold_uncertainty_score":0.3035351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0306687142806701,"score_gpt":0.280779776775876,"score_spread":0.2501110624952059,"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."}}