{"id":"W2731009140","doi":"10.1074/mcp.m116.066274","title":"Spatiotemporal Proteomic Profiling of Human Cerebral Development","year":2017,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Mount Sinai Hospital; Princess Margaret Cancer Centre; Hospital for Sick Children; University Health Network","funders":"","keywords":"Profiling (computer programming); Computational biology; Human brain; Computer science; Neuroscience; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002489889,0.0003235233,0.0003638483,0.00006598175,0.0007127002,0.000113447,0.000998757,0.0002462083,0.00007683147],"category_scores_gemma":[0.00005631138,0.0003547403,0.0001611474,0.00005053256,0.0002195998,0.0001572137,0.0004135705,0.0003853328,0.00001553749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001235146,"about_ca_system_score_gemma":0.0001671982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000663234,"about_ca_topic_score_gemma":0.000004214759,"domain_scores_codex":[0.9980997,0.000017972,0.0006352725,0.0005434598,0.0002993666,0.0004041628],"domain_scores_gemma":[0.997338,0.000005277129,0.0008333114,0.001561023,0.0001411924,0.0001211883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001859248,0.00009704512,0.005390253,0.0001924497,0.00004137416,0.00001372926,0.00006456295,0.00002392942,0.9863586,0.006707648,0.000004449052,0.001087322],"study_design_scores_gemma":[0.0005011177,0.00002771082,0.0001298005,0.000101446,0.00002401648,0.000003141938,0.00001437534,0.0003080784,0.992092,0.006078125,0.0003247049,0.0003955032],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8735473,0.00005615161,0.1211684,0.00008450884,0.00002097669,0.001013803,0.00001847745,0.0001303732,0.003960022],"genre_scores_gemma":[0.6565906,0.000003085406,0.3424442,0.00001189794,0.00004563227,0.0005105945,0.00008821942,0.00006078172,0.0002449778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2212757,"threshold_uncertainty_score":0.9998904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01803492200764802,"score_gpt":0.2780143618879198,"score_spread":0.2599794398802718,"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."}}