{"id":"W2603743177","doi":"10.71781/7722","title":"Prédictibilité des tissus mous du visage par les tissus osseux crâniens grâce aux méthodes anthropométriques standard appliquées sur le vivant","year":2005,"lang":"fr","type":"dissertation","venue":"Open MIND","topic":"Medical and Biological Sciences","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Art","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":[0.00163337,0.0009292277,0.0005540696,0.001718562,0.0003596854,0.001254,0.0005166875,0.0005253151,0.002091029],"category_scores_gemma":[0.004511424,0.0004310733,0.0008034272,0.0009495532,0.0004017718,0.0004138716,0.0003886774,0.0003948134,0.0007719873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001004338,"about_ca_system_score_gemma":0.001783925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1311699,"about_ca_topic_score_gemma":0.1361145,"domain_scores_codex":[0.9995381,0.0001043022,0.00001827414,0.0001340599,0.0001634106,0.00004202531],"domain_scores_gemma":[0.9991743,0.0004595907,0.00009246235,0.00008021686,0.0001720076,0.00002140699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001295289,0.00008086481,0.328706,0.0006221791,0.001113015,0.0001913233,0.0009602985,0.0495367,0.1134558,0.002965893,0.003310776,0.4977621],"study_design_scores_gemma":[0.00009522762,0.0002891262,0.8119333,0.0001342182,0.000539253,0.0004878368,0.0004095787,0.130994,0.04572278,0.002067367,0.007211727,0.0001155666],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6876804,0.00620054,0.2938801,0.0004129587,0.0001235799,0.0002157189,0.004602476,0.001735286,0.005148918],"genre_scores_gemma":[0.8847798,0.002307185,0.1013133,0.0000590849,0.00004478486,0.0003062292,0.001536414,0.0001929708,0.009460222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1311699,"threshold_uncertainty_score":0.2608128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08122670775232385,"score_gpt":0.3752602191628053,"score_spread":0.2940335114104815,"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."}}