{"id":"W4243420774","doi":"10.22215/etd/2014-11107","title":"Force Sensing Insole for a Balance Enhancement System","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Consejo Nacional de Ciencia y Tecnología; Secretaría de Educación Pública","keywords":"Center of pressure (fluid mechanics); Ground reaction force; Shear force; Calibration; Simulation; Force platform; Engineering; Structural engineering; Computer science; Kinematics; Mathematics; Physical medicine and rehabilitation; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004780274,0.0005079802,0.0005058221,0.0004635878,0.0002360426,0.0005633002,0.0005436114,0.0005565014,0.005700915],"category_scores_gemma":[0.0006982503,0.0002497866,0.0002686839,0.0002425828,0.0001170416,0.0003689257,0.0003500858,0.0002976376,0.001671246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001745071,"about_ca_system_score_gemma":0.0003299671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005230401,"about_ca_topic_score_gemma":0.0007834052,"domain_scores_codex":[0.9994849,0.00006677653,0.00003046222,0.0000950555,0.0002854347,0.00003723307],"domain_scores_gemma":[0.9995672,0.00007595999,0.0000313744,0.00004653688,0.0002526818,0.0000262302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004388102,0.0002346511,0.002770067,0.0004040585,0.00004991311,0.0003626578,0.0001607464,0.002244742,0.7904699,0.000938852,0.003428103,0.1984974],"study_design_scores_gemma":[0.0003221667,0.006024187,0.07161397,0.0002556335,0.0004097494,0.00247438,0.0002636941,0.123464,0.7178674,0.0007672107,0.07639394,0.000143629],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3268417,0.001559279,0.6464682,0.000581357,0.0006663378,0.001531407,0.001137549,0.005192679,0.01602156],"genre_scores_gemma":[0.7279313,0.0008804726,0.2451059,0.0003076107,0.0001511509,0.0006214143,0.0007326821,0.0001297193,0.02413978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005700915,"threshold_uncertainty_score":0.01907146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02182533106380575,"score_gpt":0.3668372892020412,"score_spread":0.3450119581382354,"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."}}