{"id":"W4408137166","doi":"10.1080/87559129.2025.2473006","title":"3D Food Printing Technology: A Critical Scientometric and Systematic Review, and Future Research Directions","year":2025,"lang":"en","type":"article","venue":"Food Reviews International","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Biotechnology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001129118,0.0001389369,0.0003861721,0.001527111,0.0001829758,0.00008818649,0.0003130377,0.0001051292,0.00001975734],"category_scores_gemma":[0.00459164,0.0001128428,0.00004437819,0.001620422,0.0002069626,0.00008580002,0.0003405721,0.0004848425,0.00001446761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007250508,"about_ca_system_score_gemma":0.00001039782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.103776e-7,"about_ca_topic_score_gemma":0.000002232216,"domain_scores_codex":[0.998871,0.00007249394,0.000376363,0.0002690828,0.0001905394,0.0002204724],"domain_scores_gemma":[0.9992357,0.0002604245,0.00004107191,0.0002628346,0.0001680915,0.00003181259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002942665,0.0001136725,0.0009772184,0.4591333,0.0008102746,0.00000595326,0.0001467354,0.000002505728,0.0001683971,0.2529402,0.0102299,0.2754689],"study_design_scores_gemma":[0.0004470115,0.0003166066,0.002504372,0.1494275,0.0005815902,0.0002019529,0.0005144149,0.0009663544,0.003777103,0.02024567,0.8202046,0.0008128216],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.006766293,0.9656322,0.002385751,0.01042226,0.001068885,0.001546934,0.00003085244,0.001070827,0.01107599],"genre_scores_gemma":[0.6301426,0.3560607,0.01154651,0.0002602108,0.0002262388,0.001118099,0.000008231114,0.00003639901,0.0006010886],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.8099747,"threshold_uncertainty_score":0.5496954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03524253021993304,"score_gpt":0.3494468382399118,"score_spread":0.3142043080199788,"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."}}