{"id":"W2223021894","doi":"","title":"Protéomique tissulaire : développements et applications pour la recherche de biomarqueurs du cancer de l’ovaire","year":2012,"lang":"fr","type":"article","venue":"ORBi (University of Liège)","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Medicine","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":[0.001976829,0.001240918,0.0008167875,0.001574239,0.0009914738,0.00157272,0.0006937248,0.001020098,0.002385452],"category_scores_gemma":[0.0006788478,0.0005906553,0.001139649,0.0008528522,0.0007448395,0.0009092725,0.0007648384,0.001256346,0.001613961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009928799,"about_ca_system_score_gemma":0.00144479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003535174,"about_ca_topic_score_gemma":0.004083952,"domain_scores_codex":[0.9994273,0.0001416992,0.00002436333,0.0001134198,0.0002236924,0.0000695495],"domain_scores_gemma":[0.9997205,0.00007336143,0.00003475655,0.00002676542,0.00009227068,0.00005233853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009417191,0.00005286678,0.0008759529,0.0002578727,0.00002272504,0.00013353,0.0001247687,0.0003850877,0.9590969,0.001121776,0.0002742116,0.03756006],"study_design_scores_gemma":[0.00005536542,0.0007091222,0.0157091,0.0001218373,0.0001104504,0.00266442,0.0002002753,0.001905112,0.8764467,0.001291673,0.1007345,0.00005145861],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5843463,0.1820104,0.2026113,0.003962695,0.001190027,0.0007282789,0.001429371,0.0009919726,0.0227297],"genre_scores_gemma":[0.6133305,0.1116127,0.2354177,0.001187478,0.0005472063,0.0007435648,0.002966862,0.0003781606,0.03381573],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003535174,"threshold_uncertainty_score":0.0104546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09962119650247256,"score_gpt":0.3508616638316847,"score_spread":0.2512404673292121,"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."}}