{"id":"W6912166139","doi":"10.5281/zenodo.14505518","title":"Поєднання ретельного медичного обстеження та використання макіяжу в естетичній медицині для досягнення оптимальних результатів корекції зовнішності (огляд літератури)","year":2024,"lang":"uk","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Body Image and Dysmorphia Studies","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Work (physics); 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.002891659,0.001492755,0.001343601,0.001644585,0.00657308,0.005717113,0.004194826,0.0008366731,0.1279835],"category_scores_gemma":[0.001751711,0.001590354,0.0007322763,0.003837537,0.002011704,0.001400152,0.005175902,0.002776389,0.2133243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008510507,"about_ca_system_score_gemma":0.000087564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000322349,"about_ca_topic_score_gemma":0.00001307266,"domain_scores_codex":[0.9878039,0.002222988,0.001795071,0.003359602,0.001843254,0.002975177],"domain_scores_gemma":[0.9931508,0.0003824885,0.00047852,0.003124341,0.00175935,0.001104481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000464624,0.0008654462,0.0000294267,0.0008575296,0.001431283,0.001285148,0.009138984,0.00002945828,0.002821298,0.05704681,0.7530681,0.1729618],"study_design_scores_gemma":[0.001995052,0.001350246,0.001731928,0.0005917315,0.0004995925,0.00103841,0.002348014,0.0006801642,0.0004259316,0.002104719,0.9855915,0.001642671],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01430602,0.0206295,0.005407189,0.01578702,0.006611904,0.003071148,0.003297704,0.006876904,0.9240126],"genre_scores_gemma":[0.8885348,0.005667038,0.000588087,0.002077901,0.004507994,0.000002469051,0.004564206,0.01099394,0.08306353],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8742288,"threshold_uncertainty_score":0.9997821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05499142814952938,"score_gpt":0.3058375883658044,"score_spread":0.250846160216275,"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."}}