{"id":"W4391571990","doi":"10.3389/frobt.2024.1281060","title":"Active learning strategies for robotic tactile texture recognition tasks","year":2024,"lang":"en","type":"article","venue":"Frontiers in Robotics and AI","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Computer science; Leverage (statistics); Artificial intelligence; Robot; Machine learning; Pipeline (software); Process (computing)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.00120146,0.001083053,0.0007933552,0.0007344126,0.0004137799,0.001078248,0.002763615,0.00122604,0.003293197],"category_scores_gemma":[0.00349151,0.0004845707,0.0006243777,0.0005584185,0.0006872146,0.001399029,0.001455127,0.001444311,0.000918558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006087808,"about_ca_system_score_gemma":0.0005690427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002726902,"about_ca_topic_score_gemma":0.002851192,"domain_scores_codex":[0.9993613,0.0001532009,0.00004203944,0.000219303,0.0001450692,0.00007901271],"domain_scores_gemma":[0.9985337,0.0008665764,0.00012895,0.000143528,0.0002423099,0.00008495338],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004931489,0.0005834982,0.001304398,0.0002345675,0.00008653502,0.0001458016,0.0002777078,0.3549075,0.02562922,0.00713741,0.003030438,0.6061699],"study_design_scores_gemma":[0.00001847932,0.00007073038,0.0002008806,0.000006580563,0.000007426444,0.00002068999,0.00002716281,0.9907539,0.003963036,0.004215118,0.0007082168,0.000007852076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03757696,0.0005346641,0.9576749,0.0002287441,0.00006047218,0.0001353764,0.00009135617,0.00137139,0.00232612],"genre_scores_gemma":[0.6909246,0.0003141482,0.3019346,0.0003549017,0.00009840322,0.0005888926,0.0003545989,0.0002100891,0.005219691],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003293197,"threshold_uncertainty_score":0.01101679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506080987834742,"score_gpt":0.2412504168598529,"score_spread":0.2261896069815055,"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."}}