{"id":"W4401262981","doi":"10.53555/sfs.v10i3.2938","title":"“Artificial Intelligence -Driven 3D Printing in Pharma: Innovations and Future Directions”","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; 3D printing; Artificial intelligence; Computer science; Engineering; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004056241,0.0008116668,0.0009307247,0.001452128,0.0006452433,0.003761644,0.001577409,0.003758507,0.004142215],"category_scores_gemma":[0.002966017,0.0004049061,0.001012785,0.002174913,0.003031529,0.005533435,0.002004565,0.00438428,0.003014677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00167125,"about_ca_system_score_gemma":0.001878461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009741005,"about_ca_topic_score_gemma":0.0008727763,"domain_scores_codex":[0.9982692,0.0004987974,0.0001118633,0.0002300019,0.0007138857,0.0001761903],"domain_scores_gemma":[0.9981397,0.0009116985,0.0001041103,0.0001284382,0.0005373394,0.0001786018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000893028,0.0001252648,0.0003701885,0.002906837,0.00007748455,0.0002803438,0.0006105822,0.003413805,0.004507792,0.2677272,0.1425418,0.5773494],"study_design_scores_gemma":[0.00001335301,0.0001376284,0.0002585435,0.000735483,0.00002048807,0.0003514218,0.0002051115,0.004376037,0.002929958,0.07224923,0.9186339,0.0000888002],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003121389,0.7735326,0.09123684,0.05440054,0.02152,0.00009914106,0.000178652,0.001058354,0.05485258],"genre_scores_gemma":[0.04547304,0.7743552,0.0858445,0.02793986,0.01040081,0.0002130855,0.0004224867,0.0003854846,0.05496556],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004142215,"threshold_uncertainty_score":0.02145171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2107325014277163,"score_gpt":0.3478349273018347,"score_spread":0.1371024258741184,"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."}}