{"id":"W2158574785","doi":"10.1177/2327857914031000","title":"Ecological Interface Design for Knee and Hip Automatic Physiotherapy Assistant and Rehabilitation System","year":2014,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rehabilitation; Interface (matter); Domain (mathematical analysis); Computer science; Automation; Work (physics); Interface design; Process (computing); Human–computer interaction; User interface; Physical therapy; Physical medicine and rehabilitation; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007229771,0.0007616048,0.000511156,0.001055035,0.0005170378,0.001452271,0.001058366,0.0006176988,0.003361041],"category_scores_gemma":[0.01167971,0.000366465,0.000685077,0.000333092,0.0005689884,0.0010072,0.001163623,0.0005384668,0.0005699595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000764398,"about_ca_system_score_gemma":0.001183685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001371608,"about_ca_topic_score_gemma":0.001529763,"domain_scores_codex":[0.9945833,0.002682191,0.0005517592,0.0003650573,0.001628307,0.0001892739],"domain_scores_gemma":[0.9944974,0.002242849,0.0002019106,0.0004298433,0.002413857,0.0002141979],"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":[0.001958989,0.001395039,0.01117715,0.002737767,0.0002156654,0.0006137489,0.007372464,0.01813543,0.2518207,0.009103913,0.002774545,0.6926946],"study_design_scores_gemma":[0.001613507,0.01865284,0.08667213,0.0006064929,0.0009990974,0.004091008,0.005261551,0.4263304,0.2542866,0.01299208,0.1879226,0.00057161],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1763767,0.0004701552,0.8141086,0.0002074253,0.0001105849,0.00185729,0.0001121529,0.002179202,0.004577828],"genre_scores_gemma":[0.3340872,0.0002345551,0.6605169,0.0001363604,0.00002409508,0.001151186,0.0002637377,0.0001576396,0.003428234],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007229771,"threshold_uncertainty_score":0.03823519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02878514652853744,"score_gpt":0.3558918906645616,"score_spread":0.3271067441360242,"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."}}