{"id":"W2167740705","doi":"10.1007/s11044-015-9451-1","title":"A fast multi-obstacle muscle wrapping method using natural geodesic variations","year":2015,"lang":"en","type":"article","venue":"Multibody System Dynamics","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Geodesic; Shortest path problem; Path (computing); Path length; Algorithm; Mathematics; Computer science; Geometry; Combinatorics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003494361,0.0002796024,0.0003349456,0.0002863447,0.0002266214,0.00009100941,0.0001829569,0.0001111295,0.000002154424],"category_scores_gemma":[0.00005817308,0.0002889204,0.000124749,0.0006417137,0.00002621148,0.0002854656,0.00004925512,0.0002398459,0.000007085569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007861858,"about_ca_system_score_gemma":0.00003946566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000379614,"about_ca_topic_score_gemma":0.0002292015,"domain_scores_codex":[0.9985062,0.00009923018,0.0003977507,0.0002797518,0.0002602223,0.0004568642],"domain_scores_gemma":[0.9991623,0.00008900153,0.00009165734,0.000310877,0.0001994406,0.0001467873],"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":[0.00002918712,0.0002090777,0.006673332,0.0009600279,0.001132024,0.00003060366,0.008659754,0.8521371,0.04613986,0.006432016,0.0003464239,0.07725053],"study_design_scores_gemma":[0.0007403733,0.00001184062,0.01122184,0.00007365629,0.00004298031,0.00002037754,0.002708857,0.9846083,0.00008651764,0.000009134332,0.0001531849,0.0003229201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1246599,0.0003132735,0.8716763,0.00002602258,0.001186495,0.0003755195,0.00003419967,0.0009618141,0.0007664639],"genre_scores_gemma":[0.9173828,0.000004462298,0.08228533,0.00001800243,0.0001041386,0.00003578109,0.00004693342,0.00006162137,0.00006093729],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7927229,"threshold_uncertainty_score":0.9999563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.031193482394658,"score_gpt":0.2749885796012608,"score_spread":0.2437950972066028,"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."}}