{"id":"W4254990411","doi":"10.1002/1522-2683(200101)22:2<208::aid-elps208>3.3.co;2-f","title":"Proteomics on a chip: Promising developments","year":2001,"lang":"en","type":"article","venue":"Electrophoresis","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Muscular Dystrophy Canada","funders":"","keywords":"Proteomics; Computer science; Data science; Computational biology; Nanotechnology; Microfluidics; Biology; Materials science; Genetics; Gene","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":[0.00004537709,0.0001086451,0.00006967433,0.00002958292,0.0001165755,0.00001505654,0.000110549,0.00007491025,0.000003567703],"category_scores_gemma":[0.00002886755,0.0001006728,0.00003759024,0.0001208792,0.00002522875,0.00000120232,0.0000362332,0.00006956775,0.000003786538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002635099,"about_ca_system_score_gemma":0.00004100906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002703697,"about_ca_topic_score_gemma":0.000004191465,"domain_scores_codex":[0.9993327,0.00001301753,0.0001028142,0.0002595191,0.00007425778,0.0002177403],"domain_scores_gemma":[0.9996235,0.000002872304,0.00004282109,0.0002528434,0.00003490269,0.00004311154],"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":[0.00008165272,0.00004194356,0.0002032892,0.00000143148,0.00001107989,0.000002213241,0.000004754874,0.000003264906,0.9916646,0.0002629044,0.001700799,0.006022011],"study_design_scores_gemma":[0.0001303263,0.0001848057,0.0009094546,0.000008195817,0.000003561658,0.00002108102,0.000002304849,0.00001131829,0.8928136,0.0004222192,0.1053548,0.0001383293],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813924,0.00009156394,0.01476234,0.0003026735,0.00001732713,0.0003322506,0.000002606366,0.0000516107,0.003047174],"genre_scores_gemma":[0.9549628,0.0003657661,0.04299596,0.0003887136,0.0001165465,0.00006280077,0.00006346785,0.00001816355,0.00102575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.103654,"threshold_uncertainty_score":0.4105317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008461146537342855,"score_gpt":0.2557030913531279,"score_spread":0.247241944815785,"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."}}