{"id":"W4390120220","doi":"10.1109/lra.2023.3346271","title":"MoSS: Monocular Shape Sensing for Continuum Robots","year":2023,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial intelligence; Computer science; Computer vision; Robot; Monocular; Segmentation; Encoder; RGB color model","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009737795,0.0001253052,0.0001364587,0.00009829414,0.0001261821,0.00009771774,0.00005822389,0.00005492476,0.000002219031],"category_scores_gemma":[0.00001281503,0.0001374858,0.00004965318,0.0002145509,0.00002459708,0.00008180813,0.00001044429,0.00006125723,0.00003345493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002187839,"about_ca_system_score_gemma":0.000004386617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000197423,"about_ca_topic_score_gemma":0.000002076677,"domain_scores_codex":[0.9993289,0.000006234432,0.000196706,0.0001531025,0.00008852552,0.0002265162],"domain_scores_gemma":[0.9996439,0.00009362229,0.00003273238,0.0001397476,0.00003136938,0.00005858916],"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":[5.467154e-7,0.000003252883,0.00004696948,0.00005297787,0.00002768898,0.000001743222,0.0001004068,0.928244,0.05224477,0.0003925201,0.01243874,0.006446389],"study_design_scores_gemma":[0.0002204425,0.000005517843,0.001622539,0.00002352411,0.00002250917,0.000003057903,0.00002016733,0.9941301,0.002031898,0.0003622599,0.001389419,0.0001685631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2521872,0.0000446874,0.7423163,0.00352314,0.000504579,0.0003407235,0.00001261202,0.001018154,0.00005257669],"genre_scores_gemma":[0.9306077,0.00006918857,0.06801261,0.0007198697,0.0003029475,0.00004302527,0.00008624551,0.00007883974,0.000079579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6784205,"threshold_uncertainty_score":0.5606508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01654830763379609,"score_gpt":0.2334446410910189,"score_spread":0.2168963334572228,"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."}}