{"id":"W4386401084","doi":"10.24908/agt.v1i2.16768","title":"Persona IQ- The Smart Knee","year":2023,"lang":"en","type":"article","venue":"Aging and (Geron) Technology","topic":"Persona Design and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Persona; Psychology; Medicine; Physical medicine and rehabilitation; Computer science; Human–computer interaction","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":[0.001231961,0.0006202698,0.000475073,0.0006178233,0.000511702,0.001592103,0.0009733314,0.001053846,0.0301595],"category_scores_gemma":[0.001967663,0.0003790236,0.000491743,0.0003565715,0.0007734144,0.001865443,0.002924903,0.0007118522,0.008530228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003198296,"about_ca_system_score_gemma":0.0006263147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001444651,"about_ca_topic_score_gemma":0.001956004,"domain_scores_codex":[0.9992855,0.0001637942,0.00004867722,0.00009989765,0.0003040885,0.00009799873],"domain_scores_gemma":[0.9992794,0.0000969137,0.00004309009,0.0001669456,0.0002631992,0.0001504939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006177605,0.0003513921,0.005971638,0.0005955747,0.0001133514,0.0008710922,0.001843323,0.005257596,0.03935756,0.06731332,0.03354498,0.8441624],"study_design_scores_gemma":[0.0003965621,0.003677924,0.02692754,0.001029582,0.0005664312,0.01268549,0.004264575,0.07090989,0.05243556,0.07033832,0.7564127,0.0003554327],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06990124,0.002267461,0.7309173,0.002184465,0.000855834,0.0005924567,0.0006824417,0.01268131,0.1799175],"genre_scores_gemma":[0.6309757,0.001686951,0.2572108,0.001420177,0.000198454,0.0005653939,0.0009767514,0.001267112,0.1056987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0301595,"threshold_uncertainty_score":0.1008936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01822176143269002,"score_gpt":0.2445319155503555,"score_spread":0.2263101541176655,"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."}}