{"id":"W2466040625","doi":"10.1680/jbibn.16.00011","title":"Advancing biomimetic materials through ISO standards","year":2016,"lang":"en","type":"article","venue":"Bioinspired Biomimetic and Nanobiomaterials","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Biomimetics; Standardization; Biomimetic materials; Consistency (knowledge bases); Engineering management; Engineering; Engineering ethics; Computer science; Function (biology); Management science; Nanotechnology; Systems engineering; Process management; Knowledge management; Artificial intelligence; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005442536,0.0004456221,0.0005859959,0.0002123963,0.0001778315,0.0001342812,0.0002769789,0.0002725266,0.0003345188],"category_scores_gemma":[0.0001961422,0.0002934074,0.00007255213,0.0001851326,0.0004058327,0.000230326,0.0001997486,0.00003318128,0.0001081957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001247895,"about_ca_system_score_gemma":0.00003126361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002337178,"about_ca_topic_score_gemma":0.000001088732,"domain_scores_codex":[0.9979753,0.00007500358,0.0005832633,0.0004713225,0.0002299256,0.0006651357],"domain_scores_gemma":[0.999135,0.0001254163,0.0001187495,0.000457883,0.00006485101,0.0000981272],"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":[0.00003784217,0.00001429199,0.00005019442,0.000126809,0.00006613121,0.00001057821,0.00004901864,2.170971e-7,0.9776134,0.0003851806,0.001455826,0.02019046],"study_design_scores_gemma":[0.0008241686,0.000124121,0.0008653953,0.0002726071,0.00004134162,0.00003166949,0.00004328319,0.000002993425,0.9732558,0.001962773,0.0220797,0.0004961896],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897606,0.0005904305,0.00435199,0.0003382273,0.001331715,0.0003261411,0.0007879962,0.002097473,0.0004153668],"genre_scores_gemma":[0.9932625,0.0009318992,0.00538803,0.00003809043,0.0001503767,0.00004694469,0.00001578478,0.00007822782,0.00008813029],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02062387,"threshold_uncertainty_score":0.9999518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008603943685227516,"score_gpt":0.2249806485428549,"score_spread":0.2163767048576274,"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."}}