{"id":"W7133054585","doi":"","title":"3D Printing of Magnetic Miniature Soft Robots Using Stereolithography","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Stereolithography; 3D printing; Magnetic nanoparticles; Robot; Flexibility (engineering); Fabrication; Magnetic separation; Magnetic field","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009977226,0.0002987905,0.000193706,0.0003659434,0.0001641117,0.0005672559,0.0002918947,0.0003338907,0.001832768],"category_scores_gemma":[0.0001600569,0.0003323615,0.0004197353,0.0002274446,0.0002651466,0.000331953,0.0003811458,0.0005248815,0.001094327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003056396,"about_ca_system_score_gemma":0.0002897371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003274113,"about_ca_topic_score_gemma":0.0008426154,"domain_scores_codex":[0.9998009,0.000008213879,0.00001601013,0.00003757356,0.0001183646,0.0000190744],"domain_scores_gemma":[0.9999015,0.00001812193,0.00003094768,0.00003023914,0.00001192682,0.000007135441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001540521,0.00002112377,0.00006743965,0.0001056762,0.000005964235,0.0001166408,0.00004589634,0.001568082,0.9666451,0.001992366,0.0004517598,0.02896443],"study_design_scores_gemma":[0.000008544763,0.00005208548,0.0005109535,0.00000909254,0.000006123334,0.000183597,0.0000115615,0.006986591,0.9817165,0.0004009463,0.01009971,0.00001442015],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4874228,0.003316781,0.4353537,0.0004636523,0.0007510856,0.0003926558,0.0009808231,0.004885825,0.06643267],"genre_scores_gemma":[0.6079813,0.002039808,0.3652622,0.0002343608,0.00005929357,0.0002326493,0.0005294005,0.0003216192,0.02333938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001832768,"threshold_uncertainty_score":0.006131172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533527638343357,"score_gpt":0.3092260194645651,"score_spread":0.2938907430811316,"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."}}