{"id":"W2161237822","doi":"10.1017/s0890060410000363","title":"A natural-language approach to biomimetic design","year":2010,"lang":"en","type":"article","venue":"Artificial intelligence for engineering design analysis and manufacturing","topic":"Design Education and Practice","field":"Engineering","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Directorate for Biological Sciences; University of Toronto; National Science Foundation","keywords":"Computer science; Natural language; Natural (archaeology); Task (project management); Biological engineering; Artificial intelligence; Engineering; Systems engineering; Bioinformatics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002344604,0.0007037038,0.0004797169,0.002942829,0.001171826,0.003463725,0.002010492,0.001180299,0.01004857],"category_scores_gemma":[0.005169732,0.000393212,0.001345639,0.001456809,0.005002545,0.0036805,0.002082168,0.001310901,0.001544753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001835102,"about_ca_system_score_gemma":0.00154714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00200661,"about_ca_topic_score_gemma":0.002452961,"domain_scores_codex":[0.9980785,0.0009954228,0.0002086215,0.0002211621,0.0004440955,0.00005226781],"domain_scores_gemma":[0.997689,0.001486068,0.000161694,0.0002530978,0.0003343205,0.00007577879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002610794,0.00004900714,0.0001598878,0.0003695154,0.00001516638,0.0002250689,0.0006975819,0.01022319,0.001673562,0.9402712,0.002633885,0.04365577],"study_design_scores_gemma":[0.00003102356,0.00006073632,0.000131887,0.0002473712,0.00001887737,0.0003412024,0.0003780721,0.04353163,0.001821938,0.8315063,0.1219019,0.00002903098],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003641075,0.001468658,0.958019,0.001775725,0.0001694592,0.0002339995,0.0002514126,0.0002856379,0.03415497],"genre_scores_gemma":[0.06052708,0.001201237,0.927969,0.0005620541,0.00009910486,0.0005340871,0.0004107476,0.00007830365,0.008618279],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01004857,"threshold_uncertainty_score":0.03361583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02878037353777203,"score_gpt":0.2687876709736877,"score_spread":0.2400072974359156,"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."}}