{"id":"W3188333238","doi":"10.33667/2078-5631-2019-2-26(401)-110-114","title":"Practical aspects and algorithms for using Cellular Matrix intradermal implant and platelet-rich plasma autologous thrombin activation technology in practice of cosmetologist","year":2019,"lang":"en","type":"article","venue":"Medical alphabet","topic":"Periodontal Regeneration and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Aging","funders":"","keywords":"Hyaluronic acid; Platelet-rich plasma; Thrombin; Matrix (chemical analysis); Thromboelastography; Cosmetology; Biomedical engineering; Computer science; Platelet activation; Algorithm; Platelet; Chemistry; Medicine; Immunology; Chromatography","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":[0.002628705,0.001096769,0.0004427622,0.003649286,0.000822221,0.002383143,0.0010937,0.00176386,0.006962019],"category_scores_gemma":[0.003793354,0.0005063771,0.0007967709,0.001330568,0.0018511,0.002618906,0.001125695,0.001663962,0.003672708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008571412,"about_ca_system_score_gemma":0.002512344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009460876,"about_ca_topic_score_gemma":0.001769724,"domain_scores_codex":[0.9977731,0.0006229756,0.0004086606,0.0003211134,0.0007818024,0.00009228471],"domain_scores_gemma":[0.9985526,0.0004864041,0.0002213246,0.0002042161,0.0003698979,0.0001656114],"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":[0.0002569258,0.0002668555,0.01036211,0.001959146,0.00004622021,0.002525962,0.0009108119,0.004048154,0.02195565,0.03835093,0.01502148,0.9042957],"study_design_scores_gemma":[0.0001913811,0.001827613,0.03000936,0.004097637,0.0004153679,0.09916935,0.002895168,0.03070218,0.04710769,0.1377533,0.6451765,0.0006543894],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01300663,0.03509024,0.8967752,0.005811197,0.001275539,0.001054152,0.0002508662,0.001802824,0.04493319],"genre_scores_gemma":[0.03906819,0.01788412,0.933318,0.0005907927,0.000538955,0.0006000093,0.000235828,0.0001930559,0.007571069],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006962019,"threshold_uncertainty_score":0.02329034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0271485581279921,"score_gpt":0.3525283469896343,"score_spread":0.3253797888616421,"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."}}