{"id":"W4256626186","doi":"10.1115/detc2014-35296","title":"Effects of Abstraction on Selecting Relevant Biological Phenomena for Biomimetic Design","year":2014,"lang":"en","type":"article","venue":"","topic":"Design Education and Practice","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Abstraction; Computer science; Analogy; Exploit; Relevance (law); Human–computer interaction; Artificial intelligence; Natural (archaeology); Epistemology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003765076,0.00007107116,0.00009345555,0.00005737396,0.00002882276,0.00001100952,0.00004252766,0.0000491294,0.00003704784],"category_scores_gemma":[0.0005217853,0.00005751505,0.00002650157,0.00008519013,0.00000740439,0.00005275147,0.000002029883,0.00006352924,0.00005062351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002509117,"about_ca_system_score_gemma":0.000006657035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002602336,"about_ca_topic_score_gemma":1.872327e-7,"domain_scores_codex":[0.99957,0.00005536578,0.0001267449,0.00008964254,0.00004437514,0.0001139059],"domain_scores_gemma":[0.9973238,0.002513704,0.00003582794,0.00006804258,0.00002595398,0.0000326949],"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":[0.0001084153,0.0001857711,0.00002135785,0.0003017229,0.00006653018,2.223096e-7,0.0002297008,0.01190503,0.8558364,0.007532417,0.003799363,0.1200131],"study_design_scores_gemma":[0.0006210101,0.0007285616,0.001939782,0.00003116515,0.00003454286,0.000002989525,0.00005891526,0.0910355,0.8838804,0.001313996,0.02013578,0.0002173254],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05223545,0.00004246303,0.9351856,0.00008237683,0.0005340261,0.0004000615,3.475375e-7,0.0002135235,0.01130616],"genre_scores_gemma":[0.9869966,0.00001699977,0.01262363,0.00006555434,0.000100017,0.00003551247,0.000001552096,0.00001243057,0.0001477124],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9347612,"threshold_uncertainty_score":0.2345396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02981173414467934,"score_gpt":0.2612871038907638,"score_spread":0.2314753697460845,"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."}}