{"id":"W7160159538","doi":"10.5281/zenodo.14905043","title":"Шкода чи користь мобільних телефонів з позиції пацієнта з артеріальною гіпертензією","year":2023,"lang":"uk","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Psychosomatic Disorders and Their Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":[],"consensus_categories":[],"category_scores_codex":[0.005501601,0.0009033533,0.0006953033,0.003126629,0.005043531,0.01662612,0.001511449,0.003032835,0.04099649],"category_scores_gemma":[0.01207277,0.0009072929,0.001057926,0.003174132,0.008323103,0.009953663,0.005483322,0.004357489,0.01960822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006444877,"about_ca_system_score_gemma":0.01336548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0119289,"about_ca_topic_score_gemma":0.01450927,"domain_scores_codex":[0.9923249,0.00209657,0.0004845509,0.001083083,0.003214781,0.0007960732],"domain_scores_gemma":[0.9932861,0.001617823,0.0006243206,0.000747622,0.002693008,0.001031116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001284238,0.0001176672,0.006282598,0.00099155,0.0000643407,0.0006506161,0.01343024,0.000810096,0.001912719,0.742322,0.06853642,0.1647533],"study_design_scores_gemma":[0.00002280083,0.00004971822,0.004236005,0.0008457616,0.00005409636,0.0004883636,0.008042942,0.000506718,0.001542095,0.1318333,0.8522988,0.00007935324],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02568074,0.02454365,0.04367632,0.04763429,0.003063447,0.0002864944,0.001304134,0.0006401093,0.8531708],"genre_scores_gemma":[0.5927521,0.03642547,0.0600222,0.008293119,0.001924977,0.000771281,0.00177053,0.001129686,0.2969106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04099649,"threshold_uncertainty_score":0.1371469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04925580343176367,"score_gpt":0.2840967516693887,"score_spread":0.2348409482376251,"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."}}