{"id":"W4393423593","doi":"10.5281/zenodo.3252175","title":"MECP2 Expression and Purification","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genetics and Neurodevelopmental Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Expression (computer science); MECP2; Biology; Computer science; Genetics","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":[0.001455895,0.003081183,0.002237255,0.003236914,0.001225291,0.002839943,0.00304674,0.002485799,0.02641463],"category_scores_gemma":[0.004175228,0.0007374711,0.001661947,0.005011342,0.0005056226,0.0009451574,0.001717265,0.0021789,0.05149329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001347081,"about_ca_system_score_gemma":0.001953488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01109978,"about_ca_topic_score_gemma":0.01790579,"domain_scores_codex":[0.998698,0.0001871234,0.0001388754,0.000569643,0.0002427876,0.0001635918],"domain_scores_gemma":[0.9989303,0.0003236592,0.000117471,0.0003348303,0.0001595409,0.0001341915],"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":[0.000839,0.0001174215,0.007638526,0.005411742,0.0004407027,0.0003047695,0.0001072996,0.003186052,0.007749416,0.001850583,0.9586371,0.01371734],"study_design_scores_gemma":[0.0007076649,0.00009156401,0.01081956,0.0005532171,0.0002636685,0.0003715307,0.00008684928,0.001794441,0.00561723,0.002795352,0.9768306,0.00006825609],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001196317,0.0004286281,0.0003468859,0.00006056474,0.00002543215,0.00002208676,0.9961908,0.0008923116,0.0008370031],"genre_scores_gemma":[0.0008227463,0.000111004,0.0007069178,0.00004011749,0.000002390503,0.00008083918,0.997772,0.000106189,0.0003577512],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02641463,"threshold_uncertainty_score":0.08836573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02293565511501853,"score_gpt":0.240521481759433,"score_spread":0.2175858266444145,"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."}}