{"id":"W4392838212","doi":"","title":"Skeletal muscle finite element modeling: adaptation From cardiac tissue activation laws","year":2023,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Finite element method; Skeletal muscle; Adaptation (eye); Cardiac muscle; Computer science; Physics; Neuroscience; Anatomy; Medicine; Biology; Thermodynamics","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":[0.001019832,0.0001512504,0.0001579972,0.0001085282,0.0001842312,0.0001352638,0.0002263537,0.00009449023,0.00007513378],"category_scores_gemma":[0.0002973081,0.000178299,0.0000587928,0.0003049394,0.00002457324,0.0002361901,0.0001009126,0.000140352,0.0001514192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006455752,"about_ca_system_score_gemma":0.00002728194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008814076,"about_ca_topic_score_gemma":0.0003263499,"domain_scores_codex":[0.9984766,0.0005105287,0.0002839735,0.000256736,0.0002295952,0.0002425615],"domain_scores_gemma":[0.9985751,0.0004855148,0.00005678589,0.0004575798,0.0003437639,0.00008128817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004817879,0.00007157027,0.00003349601,0.00006747468,0.00006087485,0.000001435973,0.009636497,0.7342728,0.1726639,0.01142125,0.0004108014,0.07135504],"study_design_scores_gemma":[0.0001790848,2.475594e-7,0.0002323353,0.0001836164,0.00001478366,9.773111e-8,0.0001863906,0.9144742,0.07685403,0.001359606,0.006342757,0.0001728199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3675493,0.00007219012,0.6274424,0.0005411282,0.000227943,0.0001473966,0.00004355693,0.0005652138,0.003410855],"genre_scores_gemma":[0.9856457,0.0002353414,0.01271912,0.00001847417,0.0000475477,0.00004437402,0.0007711661,0.00003953555,0.0004787412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6180964,"threshold_uncertainty_score":0.7270821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982462745829497,"score_gpt":0.2132474306370161,"score_spread":0.1934228031787211,"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."}}