{"id":"W2078214722","doi":"10.2174/138920209787847041","title":"Current Screens Based on the AlphaScreen&amp;#8482; Technology for Deciphering Cell Signalling Pathways","year":2009,"lang":"en","type":"article","venue":"Current Genomics","topic":"14-3-3 protein interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"PerkinElmer Biosignal","funders":"Fondation pour la Recherche Médicale; Institut National de la Santé et de la Recherche Médicale","keywords":"Signalling pathways; Signalling; Computational biology; Computer science; Cell biology; Biology; Signal transduction","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002213473,0.000258051,0.0001667253,0.00009674109,0.0002537959,0.00005033088,0.0004633285,0.0001467308,0.00002173031],"category_scores_gemma":[0.0001563912,0.0002225811,0.0002040935,0.0001288244,0.00006498626,0.000004175104,0.00007960345,0.0003093231,0.0000355586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007430663,"about_ca_system_score_gemma":0.0001295715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001344677,"about_ca_topic_score_gemma":0.000009282109,"domain_scores_codex":[0.9986415,0.00003759485,0.0003037199,0.0004839511,0.0001180607,0.0004152066],"domain_scores_gemma":[0.9989353,0.00006186258,0.0001621343,0.0006212789,0.0001355908,0.00008379366],"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":[0.0001461221,0.0003659381,0.0001354319,0.00002870029,0.00002257014,4.819157e-7,0.00003845471,0.004398271,0.908519,0.0009099744,0.003572103,0.08186292],"study_design_scores_gemma":[0.0006400916,0.00041463,0.00005678845,0.0000764571,0.00003581477,0.000003179837,0.00005161423,0.00376414,0.413069,0.0008973217,0.5806349,0.0003560928],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5611303,0.005339145,0.4295471,0.001065447,0.0009396871,0.001265774,0.0001593605,0.00007875614,0.000474348],"genre_scores_gemma":[0.9923411,0.0003543128,0.005931702,0.0002607876,0.000605571,0.0001780501,0.0002362797,0.0000439503,0.00004824587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5770628,"threshold_uncertainty_score":0.9076593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04383122042147807,"score_gpt":0.29151269079633,"score_spread":0.2476814703748519,"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."}}