{"id":"W4386401296","doi":"10.24908/agt.v1i2.16758","title":"The Use of TENG Technology in Speed Skating","year":2023,"lang":"en","type":"article","venue":"Aging and (Geron) Technology","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Speed skating; Physical medicine and rehabilitation; Preferred walking speed; Psychology; Applied psychology; Computer science; Simulation; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0002170869,0.00008427224,0.0002258125,0.0008931454,0.00008261357,0.000007589646,0.00007657025,0.0002041439,0.000003473903],"category_scores_gemma":[0.0009546102,0.00005889191,0.00003470014,0.001197112,0.0004012857,0.00003561931,0.0000898951,0.0002993284,0.00001234592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002638538,"about_ca_system_score_gemma":0.00002960377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003297868,"about_ca_topic_score_gemma":0.00002792273,"domain_scores_codex":[0.9992144,0.00001900152,0.0002516215,0.0001867526,0.00007905011,0.0002492524],"domain_scores_gemma":[0.9991981,0.0004000029,0.00006999075,0.0002637288,0.00004712594,0.00002102638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002894797,0.00003926549,0.7715062,0.0001237543,0.00004742316,0.00003879989,0.000278367,0.00003652846,0.03126127,0.005460139,0.0004651489,0.1907142],"study_design_scores_gemma":[0.007012855,0.001723312,0.7560214,0.003116572,0.0001581079,0.0006681197,0.03211349,0.01462057,0.05693943,0.0201946,0.1066439,0.0007876048],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793433,0.0006905333,0.00003048965,0.01918099,0.0001202164,0.00017,0.000001083058,0.0003342151,0.0001291491],"genre_scores_gemma":[0.9976921,0.0005252431,0.0009939992,0.0000671586,0.0000170875,0.0000122617,0.000001714001,0.00001209487,0.0006783472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1899265,"threshold_uncertainty_score":0.2401542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03000129400593691,"score_gpt":0.2915454410360871,"score_spread":0.2615441470301502,"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."}}