{"id":"W4405187366","doi":"10.1016/j.ifset.2024.103896","title":"Advances and prospects for edible robots based on additive manufacturing technology","year":2024,"lang":"en","type":"article","venue":"Innovative Food Science & Emerging Technologies","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Key Research and Development Program of China Stem Cell and Translational Research; Fundamental Research Funds for the Central Universities","keywords":"Manufacturing engineering; Robot; Engineering; Business; Computer science; Artificial intelligence","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":[0.0007358133,0.000548429,0.0005176276,0.0006878312,0.0002196709,0.001244262,0.0008190684,0.001189089,0.004394879],"category_scores_gemma":[0.0005469937,0.000222448,0.0005316493,0.0006987682,0.0006366998,0.002306187,0.0006395296,0.0008251514,0.001205916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004032351,"about_ca_system_score_gemma":0.0004485511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002681309,"about_ca_topic_score_gemma":0.0003379419,"domain_scores_codex":[0.9997271,0.0000418006,0.00001266038,0.00006367038,0.0001100924,0.00004474126],"domain_scores_gemma":[0.9995919,0.0001704053,0.00005746663,0.00002753687,0.0001134636,0.00003928623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000420051,0.0002788404,0.002269885,0.00486236,0.00007473119,0.0004945404,0.0002690755,0.007140359,0.07998718,0.1244357,0.01075234,0.7690148],"study_design_scores_gemma":[0.00007454692,0.001282357,0.005272266,0.001604385,0.0001477054,0.001961297,0.0006072491,0.03427741,0.05829419,0.09102181,0.8052924,0.0001644503],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0328308,0.8437451,0.06090982,0.004424997,0.0008625906,0.00003745888,0.0001048073,0.0003022117,0.05678228],"genre_scores_gemma":[0.2887755,0.6112857,0.07221661,0.001631967,0.00134454,0.00009155215,0.0003095847,0.00006901472,0.02427565],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004394879,"threshold_uncertainty_score":0.01470238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01439599160944641,"score_gpt":0.2642459053253323,"score_spread":0.2498499137158859,"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."}}