{"id":"W1978249038","doi":"10.1115/1.3005165","title":"Effect of Calibration Method on Tekscan Sensor Accuracy","year":2008,"lang":"en","type":"article","venue":"Journal of Biomechanical Engineering","topic":"Knee injuries and reconstruction techniques","field":"Medicine","cited_by":173,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Vancouver Coastal Health; Vancouver Coastal Health Research Institute; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Michael Smith Health Research BC","keywords":"Calibration; Range (aeronautics); Computer science; Accuracy and precision; Software; Artificial intelligence; Mathematics; Statistics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000451562,0.00009666399,0.0004196203,0.0002917828,0.00001943882,0.000003544506,0.00004996105,0.00009968905,0.00002986986],"category_scores_gemma":[0.0004077723,0.00006490997,0.0002180991,0.000182011,0.00001687139,0.00007132603,0.00001137203,0.0002406843,7.948583e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004104811,"about_ca_system_score_gemma":0.00003192914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003373024,"about_ca_topic_score_gemma":2.371885e-8,"domain_scores_codex":[0.9990925,0.00003623794,0.0004889501,0.00006839413,0.0002159638,0.00009792609],"domain_scores_gemma":[0.9991952,0.0002898922,0.0002359429,0.00009771236,0.00007562934,0.0001056838],"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":[0.000463598,0.00005279929,0.00008293631,0.0001894964,0.0001010162,0.0000769961,0.0000290781,0.0002134589,0.9645448,0.0002912144,0.0001972079,0.03375737],"study_design_scores_gemma":[0.0006616567,0.003255463,0.0000942387,0.0002233424,0.00005170989,0.00247815,0.000006503511,0.008127695,0.9841133,0.00001428804,0.0009124462,0.00006114113],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7640701,0.00007826773,0.2348922,0.0002896165,0.0004190082,0.0001396673,0.000002722361,0.00005009898,0.00005835604],"genre_scores_gemma":[0.9591146,0.00009669806,0.04044045,0.00003210644,0.0002697546,0.000001369141,7.563902e-7,0.00001617429,0.00002805638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1950445,"threshold_uncertainty_score":0.2646952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00982516026138277,"score_gpt":0.2967391504028583,"score_spread":0.2869139901414755,"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."}}