{"id":"W7092554270","doi":"10.1007/s00170-025-16810-2","title":"High-accuracy real-time controlled robotic-based bioprinting onto unknown and moving surfaces","year":2025,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cegep Edouard Montpetit","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Planar; A priori and a posteriori; Motion planning; Coherence (philosophical gambling strategy); 3D printing; Heartbeat; Control system","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":[0.0002000374,0.0001392686,0.0002878377,0.0003435596,0.00008460942,0.0000615734,0.0006002729,0.00007674595,0.00001416644],"category_scores_gemma":[0.0001599002,0.0001057038,0.00006528845,0.0001016105,0.00008265718,0.0001068058,0.0001077861,0.0002800872,0.000003336498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00010887,"about_ca_system_score_gemma":0.0000310991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001591024,"about_ca_topic_score_gemma":0.00001068925,"domain_scores_codex":[0.9991349,0.00001084918,0.0004270615,0.0001115112,0.0001554882,0.0001601882],"domain_scores_gemma":[0.998981,0.0004520427,0.0002155733,0.0001854892,0.0001393831,0.0000264957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006803139,0.00002053408,0.0000857339,0.00001113833,0.0002261443,0.00000810867,0.00001877182,0.7973503,0.178617,0.007568588,0.0000586695,0.01596698],"study_design_scores_gemma":[0.004150407,0.00005266152,0.002471373,0.0003040442,0.00009963319,0.00006076815,0.0001786078,0.05490998,0.9025238,0.03244201,0.002551173,0.0002555609],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9666456,0.000324053,0.02698674,0.00489036,0.0004990035,0.0001548971,0.000001652277,0.000189686,0.0003080023],"genre_scores_gemma":[0.973667,0.0003744468,0.02572488,0.00005769653,0.0000531114,0.00001101149,0.000001186363,0.00001521407,0.00009543066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7424403,"threshold_uncertainty_score":0.4310476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004009964288714421,"score_gpt":0.23283804846103,"score_spread":0.2288280841723156,"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."}}