{"id":"W4285034155","doi":"10.1177/09544089221110423","title":"Environmentally conscious biomedical implant manufacturing method","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Implant; Process (computing); Materials science; Computer science; Process engineering; Manufacturing engineering; Engineering; Medicine; Surgery","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":[0.0004197881,0.0005373867,0.0002829911,0.0007732965,0.000509406,0.0005428223,0.0005725417,0.0006299291,0.005178322],"category_scores_gemma":[0.0002929843,0.0002628719,0.0004315568,0.0004057269,0.0003239105,0.0003509864,0.0007108962,0.0006779911,0.003477899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003345276,"about_ca_system_score_gemma":0.0005664947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000275186,"about_ca_topic_score_gemma":0.0006925618,"domain_scores_codex":[0.9991121,0.00005182805,0.00006627449,0.000167605,0.0005584891,0.00004384254],"domain_scores_gemma":[0.9998342,0.0000187314,0.00003741758,0.00005126409,0.00004634758,0.00001202522],"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":[0.00007320752,0.00008528744,0.0004969782,0.0004218776,0.00001052564,0.000236658,0.00008144084,0.0004763634,0.93698,0.003212854,0.001234191,0.05669069],"study_design_scores_gemma":[0.00004229663,0.0008276051,0.003861219,0.00007724958,0.00005264854,0.002033713,0.00006395207,0.00238598,0.8431553,0.001379811,0.1460573,0.00006286368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1808362,0.01170418,0.7007397,0.001086007,0.001878127,0.002497268,0.001524811,0.00387766,0.09585596],"genre_scores_gemma":[0.4599945,0.005827878,0.4821666,0.001048116,0.0002308061,0.001696246,0.001065494,0.000288383,0.04768198],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005178322,"threshold_uncertainty_score":0.01732326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008979828648482648,"score_gpt":0.2182178916605521,"score_spread":0.2092380630120694,"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."}}