{"id":"W4281742403","doi":"10.1016/j.jbiomech.2022.111158","title":"A generalised smoothing approach for continuous, planar, inverse kinematics problems","year":2022,"lang":"en","type":"article","venue":"Journal of Biomechanics","topic":"Sports Dynamics and Biomechanics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Running Injury Clinic; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Kinematics; Inverse kinematics; Smoothing; Mathematics; Inverse; Inverse problem; Applied mathematics; Planar; Probabilistic logic; Bayesian probability; Basis (linear algebra); Computer science; Mathematical analysis; Geometry; Statistics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001141971,0.0008347307,0.001240531,0.0009433509,0.0004527449,0.001115315,0.001558975,0.001711825,0.003365696],"category_scores_gemma":[0.003348456,0.0007587677,0.001473609,0.001045448,0.0009918247,0.001225748,0.001906941,0.001891352,0.001039474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003324166,"about_ca_system_score_gemma":0.001019727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003646025,"about_ca_topic_score_gemma":0.004166238,"domain_scores_codex":[0.9995048,0.0001590631,0.00003420829,0.00008410269,0.0001828043,0.00003504765],"domain_scores_gemma":[0.9988242,0.0007280423,0.00006432235,0.0001152338,0.0002107108,0.00005748688],"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":[0.0002224005,0.0001088446,0.0005324495,0.0005331941,0.0001938792,0.0002369352,0.0002523257,0.6311909,0.01964357,0.1053133,0.003411266,0.2383609],"study_design_scores_gemma":[0.00001053559,0.00004155281,0.0001024518,0.00001053338,0.00001477874,0.00003788503,0.00001112192,0.9802744,0.0007142861,0.01640384,0.00236456,0.00001416887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001729975,0.000108832,0.9976273,0.00004341389,0.00002824142,0.000007525778,0.00001120787,0.00007140675,0.0003720844],"genre_scores_gemma":[0.1372533,0.0008620254,0.8480158,0.0001174711,0.0002196273,0.0001457542,0.0002571988,0.0003779243,0.0127509],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003646025,"threshold_uncertainty_score":0.01125938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01366156716982772,"score_gpt":0.1964851823015728,"score_spread":0.1828236151317451,"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."}}