{"id":"W3159217696","doi":"10.1126/scirobotics.abi5066","title":"Unraveling DNA inspires artificial muscle","year":2021,"lang":"en","type":"letter","venue":"Science Robotics","topic":"Advanced Materials and Mechanics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Artificial muscle; Skeletal muscle; DNA; Anatomy; Computer science; Artificial intelligence; Biology; Biochemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.000199413,0.0002358539,0.0002669755,0.0001365411,0.0001677006,0.000217529,0.0004354024,0.0002937852,0.00004884104],"category_scores_gemma":[0.00008815509,0.0002427814,0.00005769053,0.0004421861,0.0001338568,0.0001743931,0.0001223227,0.0005884389,0.00005829421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000137951,"about_ca_system_score_gemma":0.0001809649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000334241,"about_ca_topic_score_gemma":0.000004902579,"domain_scores_codex":[0.9982868,0.00001039627,0.0002704968,0.0003632031,0.0004594533,0.0006096071],"domain_scores_gemma":[0.9993317,0.00002742498,0.0000501399,0.0004125909,0.0001075347,0.00007057919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[5.93145e-7,0.00001031941,2.700262e-7,0.0003016783,0.00001238856,0.0003400107,0.0001801681,0.5427157,0.3582934,0.00199318,0.08739392,0.008758322],"study_design_scores_gemma":[0.00009547138,0.00003405294,0.000007109139,0.0003158656,0.00005229368,0.00002560058,0.00008039381,0.07965089,0.1679991,0.007274646,0.7433037,0.001160877],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.01175353,0.00178457,0.6729526,0.2236713,0.07880297,0.001085995,0.0002322522,0.002886391,0.006830339],"genre_scores_gemma":[0.06022071,0.00177178,0.2956609,0.6022235,0.0358819,0.00008057103,0.0005621446,0.0009489213,0.002649627],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6559097,"threshold_uncertainty_score":0.9900339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02631465807921079,"score_gpt":0.2358514135664093,"score_spread":0.2095367554871985,"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."}}