{"id":"W4384282863","doi":"10.2196/preprints.50834","title":"Advances in Applying Somatosensory Interaction Technology in Geriatric Health Management: Bibliometric Analysis (Preprint)","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health management system; Computer science; Medicine; Psychology; Alternative medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0142412,0.0006984796,0.002354629,0.1089772,0.001066819,0.006351287,0.0009248498,0.0007630359,0.01076623],"category_scores_gemma":[0.07722791,0.000317504,0.002643049,0.1461487,0.0007098101,0.004769359,0.001941489,0.000623192,0.001981309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002983576,"about_ca_system_score_gemma":0.008222784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004882541,"about_ca_topic_score_gemma":0.006186042,"domain_scores_codex":[0.9864872,0.003142999,0.00406938,0.001060899,0.004873946,0.0003654626],"domain_scores_gemma":[0.918568,0.05237605,0.009064197,0.001857995,0.01736714,0.0007666911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003466489,0.0001497613,0.09808712,0.1718607,0.004679251,0.0004501142,0.003471511,0.001308794,0.001483287,0.007821496,0.09701984,0.6133215],"study_design_scores_gemma":[0.0001201962,0.0003098261,0.4419123,0.08351251,0.01444956,0.001213382,0.009174484,0.004583103,0.003399523,0.01262311,0.4284032,0.000298772],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1475922,0.6230044,0.01612133,0.02780639,0.004333693,0.002507612,0.1256208,0.001316929,0.0516967],"genre_scores_gemma":[0.4332984,0.4604236,0.03180557,0.002464811,0.003886723,0.002860825,0.05958059,0.0003446196,0.005334986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8910229,"threshold_uncertainty_score":0.07531559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05413672233215872,"score_gpt":0.4067047564125366,"score_spread":0.3525680340803778,"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."}}