{"id":"W4394822974","doi":"10.1088/1748-3190/ad3ed3","title":"Parameters for selecting biological features in multifunctional bio-inspired design: a convergent evolution approach","year":2024,"lang":"en","type":"article","venue":"Bioinspiration & Biomimetics","topic":"Design Education and Practice","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Process (computing); Computer science; Feature (linguistics); Biomimetics; Domain (mathematical analysis); Biochemical engineering; Artificial intelligence; Function (biology); Selection (genetic algorithm); Biological system; Engineering; Mathematics; Biology","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":[0.0005949299,0.0001951127,0.0001519861,0.0003430167,0.00008913476,0.0001528849,0.00008920074,0.0002101183,0.00002659589],"category_scores_gemma":[0.0002492147,0.0001824498,0.00008431292,0.0006778035,0.00004131551,0.0002195295,0.000009478244,0.0001734476,0.00004933828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000285302,"about_ca_system_score_gemma":0.0001057785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001627946,"about_ca_topic_score_gemma":0.000005262013,"domain_scores_codex":[0.998834,0.0001034303,0.0003494379,0.0003157313,0.0001393845,0.0002580069],"domain_scores_gemma":[0.9993443,0.0003424708,0.00004193612,0.000127962,0.00007081436,0.00007249332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006704435,0.001145793,0.003537048,0.001196294,0.0006521502,0.000008241323,0.003363658,0.1908584,0.5944765,0.04283286,0.04321223,0.1180464],"study_design_scores_gemma":[0.0006508557,0.0002473831,0.003879227,0.00004498996,0.0000560673,0.00002179737,0.0002757829,0.9393129,0.01837702,0.000608938,0.03606524,0.0004598538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02298389,0.001644957,0.9712381,0.0002895044,0.001955176,0.0008561343,0.00002600758,0.0005852424,0.0004209731],"genre_scores_gemma":[0.8771286,0.00006089168,0.1220151,0.0001068043,0.0001772517,0.0002206346,0.0001443869,0.0000334361,0.0001129098],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8541447,"threshold_uncertainty_score":0.7440088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0689981287130056,"score_gpt":0.2829771189853746,"score_spread":0.213978990272369,"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."}}