{"id":"W1980237987","doi":"10.1021/ac000948b","title":"Nanoflow Gradient Generator Coupled with μ-LC−ESI-MS/MS for Protein Identification","year":2001,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Institute for Marine Biosciences","funders":"Dalhousie University","keywords":"Chemistry; Chromatography; Tandem mass spectrometry; Mass spectrometry; Proteome; Tandem; Electrospray; Isoelectric focusing; Proteomics; High-performance liquid chromatography; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008963357,0.0009147771,0.0007261964,0.0008914542,0.0004460859,0.0006821186,0.0009471122,0.0005881966,0.004265819],"category_scores_gemma":[0.0007845127,0.0003662329,0.000358674,0.0006327309,0.000324207,0.0008990489,0.0006391613,0.001301187,0.004301675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003945359,"about_ca_system_score_gemma":0.0004797614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000335565,"about_ca_topic_score_gemma":0.0008039193,"domain_scores_codex":[0.9994712,0.0000911547,0.00005255443,0.0001196161,0.0002277867,0.00003765824],"domain_scores_gemma":[0.9997141,0.0001025189,0.00004145293,0.00003141842,0.00006460513,0.00004584144],"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":[0.00008332768,0.00004604465,0.0001387004,0.0001391664,0.000008832524,0.00004542297,0.00001449014,0.00005381779,0.9753978,0.0004127658,0.0009294496,0.02273017],"study_design_scores_gemma":[0.00004117774,0.000308426,0.001402324,0.00002463673,0.00003924425,0.0009116529,0.00001319139,0.003314491,0.970018,0.0005118052,0.02337273,0.00004232763],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1416651,0.00973503,0.8243664,0.001155571,0.0007433033,0.001178677,0.002586053,0.01015745,0.008412542],"genre_scores_gemma":[0.101001,0.005289391,0.8766173,0.0008582647,0.0001659922,0.0007955923,0.003786392,0.0005645733,0.01092147],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004265819,"threshold_uncertainty_score":0.01427054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01313801597968605,"score_gpt":0.2564210654506233,"score_spread":0.2432830494709373,"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."}}