{"id":"W2137468922","doi":"10.1145/2633651.2633658","title":"Toward automated categorization of mobile health and fitness applications","year":2014,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Categorization; Computer science; Android (operating system); Crawling; Feature selection; Keyword extraction; Health records; Mobile device; Mobile phone; Artificial intelligence; Machine learning; Information retrieval; Health care; World Wide Web; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002743605,0.001133148,0.00126031,0.01372081,0.001110148,0.002660336,0.001343946,0.00137089,0.0009556846],"category_scores_gemma":[0.01106471,0.0003505723,0.0009222461,0.004656235,0.0003795267,0.002357304,0.001235479,0.000923988,0.002171775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009200922,"about_ca_system_score_gemma":0.00188755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008259785,"about_ca_topic_score_gemma":0.01104331,"domain_scores_codex":[0.9958151,0.001094677,0.0005519497,0.000844907,0.00132836,0.0003649466],"domain_scores_gemma":[0.987538,0.00496315,0.001044364,0.0009086443,0.0053045,0.0002413875],"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":[0.0004157029,0.001064038,0.09715074,0.001049671,0.0001351254,0.0006687744,0.001494453,0.00383065,0.04061276,0.002292389,0.0246403,0.8266453],"study_design_scores_gemma":[0.0001881064,0.0008278618,0.2552665,0.0006700909,0.0003505777,0.002323323,0.009150279,0.5462053,0.1058761,0.01753618,0.06136258,0.0002432091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6970812,0.004945202,0.256446,0.001997363,0.0003034524,0.002328023,0.01098557,0.01318168,0.01273155],"genre_scores_gemma":[0.6212236,0.001032751,0.3460581,0.0005073014,0.0001776292,0.0008250885,0.02363871,0.0003243293,0.006212451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01372081,"threshold_uncertainty_score":0.0164234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486673520986013,"score_gpt":0.2706124816316873,"score_spread":0.2557457464218272,"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."}}