{"id":"W4367024162","doi":"10.5114/for.2022.126062","title":"Differences in the facial soft tissue thickness depending on the skeletal class and sexLiterature review","year":2022,"lang":"en","type":"article","venue":"Orthodontic Forum","topic":"Orthodontics and Dentofacial Orthopedics","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Soft tissue; Class (philosophy); Medicine; Surgery; Computer science; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.002213571,0.0002933733,0.0004330399,0.00009007214,0.0009068927,0.0002857161,0.0006120108,0.0001021066,0.0005076791],"category_scores_gemma":[0.0004136649,0.0001739066,0.000153366,0.0005135141,0.0001172478,0.0001230173,0.0003897381,0.001086526,0.0000402379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003971521,"about_ca_system_score_gemma":0.00005399374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007362565,"about_ca_topic_score_gemma":0.0006862956,"domain_scores_codex":[0.9966365,0.0009805118,0.0004730697,0.0004536623,0.0009335243,0.0005228102],"domain_scores_gemma":[0.998478,0.0006602581,0.0002018755,0.0005518951,0.00003701796,0.0000709404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009736072,0.0002802823,0.8427176,0.0005830341,0.00009302999,0.001117303,0.001880682,0.000009330841,0.0001054721,0.08071368,0.02378275,0.04861943],"study_design_scores_gemma":[0.0007032619,0.0003376902,0.183377,0.0004815789,0.0001664033,0.0006586667,0.002321138,0.0002644501,0.00001501306,0.0007629312,0.810294,0.0006178232],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.952439,0.01651632,0.000713873,0.01758459,0.002531527,0.001846487,0.0002494483,0.00009110435,0.008027622],"genre_scores_gemma":[0.9897354,0.0007751649,0.00007415687,0.006760461,0.0001521787,0.0001726576,0.00004471193,0.000031462,0.002253865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7865112,"threshold_uncertainty_score":0.7091705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02737423461532627,"score_gpt":0.2860153704081839,"score_spread":0.2586411357928576,"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."}}