{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001273681,0.0002474162,0.0002597583,0.00002890073,0.0001720241,0.00009561067,0.0003290532,0.0001955291,0.004342072],"category_scores_gemma":[0.00007053756,0.0002201162,0.0001436405,0.0003497534,0.0001078483,0.00006252614,0.00003928856,0.0002004422,0.00002157484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001579966,"about_ca_system_score_gemma":0.00006550776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002487244,"about_ca_topic_score_gemma":0.000005487416,"domain_scores_codex":[0.9983302,0.000003929168,0.0003890354,0.0005730482,0.000292869,0.0004108578],"domain_scores_gemma":[0.998716,0.00003672517,0.0001490279,0.0007048935,0.0001750361,0.0002183247],"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":[0.00007009359,0.0002939595,0.0006372908,0.0002222612,0.00007451789,0.000009136739,0.000007863424,0.000009164771,0.9919637,0.004455727,0.00186143,0.0003948473],"study_design_scores_gemma":[0.0005370353,0.00002924248,0.00007314964,0.00004777929,0.0001064184,0.00003221279,0.00002658145,0.02202457,0.9360987,0.001786721,0.0388592,0.0003783937],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9394681,0.00007956284,0.01822299,0.00116574,0.00001089348,0.0004434153,0.0000742162,0.0003974093,0.04013771],"genre_scores_gemma":[0.9741344,0.0000208048,0.003283305,0.00005065182,0.0003223397,0.0008468125,0.0002779872,0.00004557685,0.02101814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05586501,"threshold_uncertainty_score":0.9965681,"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."}}