{"id":"W2082806404","doi":"10.1115/detc2012-71296","title":"Exploring the Collective Categorization of Biological Information for Biomimetic Design","year":2012,"lang":"en","type":"article","venue":"","topic":"Design Education and Practice","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Categorization; Computer science; Semantics (computer science); Task (project management); Search engine indexing; Artificial intelligence; Natural language processing; Engineering","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":[0.01104837,0.0007090714,0.000428631,0.001359071,0.001777508,0.002997357,0.001017217,0.001355635,0.002556009],"category_scores_gemma":[0.02215094,0.0003284029,0.0006475087,0.0006966936,0.003163551,0.004960284,0.002611641,0.00125568,0.0002958448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001100586,"about_ca_system_score_gemma":0.001020552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004508808,"about_ca_topic_score_gemma":0.0008886899,"domain_scores_codex":[0.9940896,0.004298213,0.000185629,0.0004590267,0.000782315,0.0001852092],"domain_scores_gemma":[0.9824544,0.01344147,0.0009923173,0.001849681,0.0009287919,0.0003333838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004807235,0.0007377905,0.0264642,0.001863893,0.0001471102,0.0008033869,0.2357359,0.02595196,0.08755221,0.2626727,0.003471888,0.3541182],"study_design_scores_gemma":[0.0001359737,0.001128619,0.01623867,0.0005856073,0.0001433026,0.001220111,0.1122692,0.2319814,0.03666503,0.5364136,0.06301271,0.0002058113],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5572668,0.0002820935,0.4274137,0.001476007,0.0000350729,0.0002271555,0.00005101033,0.000186661,0.0130616],"genre_scores_gemma":[0.8407111,0.00009508704,0.1576328,0.00007604163,0.00001001328,0.0001802863,0.00008548808,0.00003730497,0.001171862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01104837,"threshold_uncertainty_score":0.05843008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2571975386970133,"score_gpt":0.2856911507161517,"score_spread":0.02849361201913836,"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."}}