{"id":"W2053478260","doi":"10.1126/stke.2001.103.pe33","title":"Cell Signalling - The Proteomics of It All","year":2001,"lang":"en","type":"article","venue":"Science s STKE","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Muscular Dystrophy Canada; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"","keywords":"Computational biology; Proteomics; DNA microarray; Biology; Signalling; Resource (disambiguation); Data science; Computer science; Gene; Gene expression; Genetics; Cell 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":[],"consensus_categories":[],"category_scores_codex":[0.0002586305,0.00006264749,0.00006129136,0.00002139536,0.0001852054,0.00002500093,0.0006269446,0.00002904685,0.0001380027],"category_scores_gemma":[0.00002425124,0.00004489115,0.0000307085,0.0002811751,0.0003763445,0.0000953085,0.00009334856,0.0001193781,0.000009826467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003050367,"about_ca_system_score_gemma":0.00007447819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001842825,"about_ca_topic_score_gemma":0.000001752666,"domain_scores_codex":[0.9992735,0.000002369047,0.0001436927,0.0001878409,0.0001942495,0.0001983126],"domain_scores_gemma":[0.9994275,0.0000252212,0.0001011373,0.0003326931,0.00007159715,0.0000418499],"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":[0.000002569583,0.00002042809,0.000128891,0.000006573957,6.611442e-7,2.880514e-7,0.0001056179,0.0001800057,0.9965222,0.002353218,0.00007994637,0.0005995913],"study_design_scores_gemma":[0.00004602455,0.000007690558,0.000008031113,0.0000101615,0.000003137183,0.000003053821,0.0001395993,0.001463182,0.9768451,0.009427086,0.01198187,0.0000650141],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8112606,0.00006019658,0.08900229,0.001493429,0.00002088267,0.0003187082,0.00001116108,0.00009210364,0.09774066],"genre_scores_gemma":[0.9422761,0.00006993645,0.05628755,0.0001280139,0.00003209432,0.00006492757,0.000001180348,0.00000648697,0.001133683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1310156,"threshold_uncertainty_score":0.1830608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02283423142931736,"score_gpt":0.2963228774504769,"score_spread":0.2734886460211596,"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."}}