{"id":"W3040846519","doi":"10.1145/3396250","title":"mSIMPAD","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Computing for Healthcare","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Research Grants Council, University Grants Committee","keywords":"Euclidean distance; Computer science; Scalability; Pattern recognition (psychology); Similarity (geometry); Series (stratigraphy); A priori and a posteriori; Simple (philosophy); Ranging; Wearable computer; Inertial measurement unit; Data mining; Artificial intelligence","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":[0.001271907,0.002106362,0.001420898,0.002933546,0.0007604985,0.002571038,0.003956309,0.001689607,0.04073658],"category_scores_gemma":[0.00502626,0.0007338763,0.001236178,0.002453085,0.0003707551,0.002961795,0.002803489,0.00142224,0.04494639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005758519,"about_ca_system_score_gemma":0.001409192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0031645,"about_ca_topic_score_gemma":0.004719749,"domain_scores_codex":[0.9985562,0.0001389344,0.0001140179,0.0004851772,0.000584422,0.0001211366],"domain_scores_gemma":[0.9986725,0.0002762334,0.0001099628,0.0004381487,0.0003880544,0.0001150022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001395787,0.0002844829,0.003873499,0.001145491,0.0002473644,0.0003117847,0.0001502439,0.005035136,0.008212414,0.005863348,0.6468361,0.3266444],"study_design_scores_gemma":[0.0004435923,0.0004824986,0.004032911,0.0001820883,0.0001357464,0.001257392,0.0001891376,0.1172429,0.02305312,0.01496015,0.8378423,0.0001781881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.0238221,0.00872663,0.3241389,0.001758664,0.002962778,0.001470629,0.2005977,0.372524,0.06399859],"genre_scores_gemma":[0.1022129,0.003216541,0.3349588,0.001912182,0.0006208218,0.001600676,0.4894048,0.009524521,0.05654873],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04073658,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06767410526982057,"score_gpt":0.298956634895423,"score_spread":0.2312825296256024,"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."}}