{"id":"W4402721967","doi":"10.1145/3670947.3670978","title":"A Data Visualization Tool for Patients and Healthcare Providers to Communicate during Inpatient Stroke Rehabilitation","year":2024,"lang":"en","type":"article","venue":"Graphics Interface","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Bruyère; McGill University; Carleton University","funders":"Universitas Brawijaya","keywords":"Visualization; Rehabilitation; Health care; Data visualization; Stroke (engine); Computer science; Medical emergency; Physical medicine and rehabilitation; Medicine; Physical therapy; Data mining; Engineering","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":[0.0003008897,0.0001213413,0.0001778456,0.0003202527,0.00009968631,0.00006856374,0.0001213649,0.00007593009,0.000004652637],"category_scores_gemma":[0.0009262603,0.0001083537,0.00005952354,0.0002644123,0.00006781014,0.0002340578,0.0001651667,0.0001456359,0.000004869004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009635585,"about_ca_system_score_gemma":0.00005650553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003123175,"about_ca_topic_score_gemma":0.00004964655,"domain_scores_codex":[0.9988384,0.00007065301,0.0003433553,0.0003848439,0.0002001957,0.0001625183],"domain_scores_gemma":[0.9986503,0.0004839439,0.00004714741,0.0004982411,0.0002222545,0.00009811562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004776423,0.001705867,0.7932655,0.02857254,0.0007987586,0.000004322649,0.0406248,0.000148338,0.00964828,0.02565313,0.0252657,0.0695363],"study_design_scores_gemma":[0.00840391,0.01702386,0.7334666,0.008179765,0.0004512538,0.00002372475,0.008162532,0.049543,0.003028637,0.002543926,0.1679107,0.001262093],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843692,0.0007049558,0.005397275,0.006640994,0.0004269349,0.00192374,0.0004051626,0.0001103047,0.00002145504],"genre_scores_gemma":[0.9953798,0.000148503,0.003543756,0.0003248536,0.00003027536,0.0001140637,0.0002944615,0.00002862773,0.0001356416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.142645,"threshold_uncertainty_score":0.4418534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03529647522082469,"score_gpt":0.3632514509037214,"score_spread":0.3279549756828967,"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."}}