{"id":"W3023329308","doi":"10.5539/cis.v13n2p46","title":"Multi-Agent System for Post-Stroke Medical Monitoring in Web-Based Platform","year":2020,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Damages; Set (abstract data type); Autonomy; Rehabilitation; Work (physics); Control (management); Stroke (engine); Plan (archaeology); Human–computer interaction; Medicine; Artificial intelligence; Physical therapy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009129128,0.0001126097,0.0001497074,0.0002644067,0.0002099565,0.0004317566,0.0007123719,0.00005610563,0.000001528927],"category_scores_gemma":[0.00009909077,0.00009660939,0.00003852745,0.000481751,0.00005807758,0.005548915,0.0002167046,0.00008833235,0.00002706653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008489154,"about_ca_system_score_gemma":0.0002649502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001009382,"about_ca_topic_score_gemma":0.000001512452,"domain_scores_codex":[0.9983678,0.00001641663,0.0004655001,0.0002428104,0.000648065,0.0002593413],"domain_scores_gemma":[0.9991161,0.00007436523,0.0001440046,0.000182164,0.0002123219,0.0002710474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001276806,0.0002363975,0.07863234,0.002753,0.00003197903,0.00002387957,0.04681902,0.01977701,0.01812555,0.04426489,0.0006569973,0.7885513],"study_design_scores_gemma":[0.001171577,0.0000783169,0.01513432,0.00007856161,8.98661e-7,0.00000547105,0.0001133258,0.9796716,0.001915848,8.182619e-7,0.001714742,0.0001145458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09760635,0.00002018235,0.9003152,0.0006402805,0.0008504458,0.0003552879,0.000007153353,0.0001234452,0.00008160686],"genre_scores_gemma":[0.9382995,0.000004868854,0.06059065,0.0009660229,0.0001048519,0.00002625657,0.000003475792,0.000002320731,0.000002053582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9598945,"threshold_uncertainty_score":0.4163439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03738752825093426,"score_gpt":0.2710527099810097,"score_spread":0.2336651817300754,"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."}}