{"id":"W2025186215","doi":"10.1021/ac035014c","title":"Device for the Reversed-Phase Separation and On-Target Deposition of Peptides Incorporating a Hydrophobic Sample Barrier for Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry","year":2004,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Institute of General Medical Sciences","keywords":"Chemistry; Chromatography; Mass spectrometry; Matrix-assisted laser desorption/ionization; MALDI imaging; Electrospray ionization; Analyte; Sample preparation; Analytical Chemistry (journal); Electrospray; Elution; Desorption; Ion suppression in liquid chromatography–mass spectrometry; Matrix (chemical analysis); Phase (matter); Tandem mass spectrometry; Adsorption","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003800655,0.0006683376,0.0005544622,0.0005204595,0.0003586691,0.0004339238,0.00118014,0.001010032,0.004568956],"category_scores_gemma":[0.0002896691,0.0004709193,0.0003336027,0.000243398,0.000260653,0.0004261991,0.0004313202,0.0007668652,0.003726946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003181906,"about_ca_system_score_gemma":0.0004177604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001581148,"about_ca_topic_score_gemma":0.0003839385,"domain_scores_codex":[0.9996068,0.0000326097,0.0000246228,0.00009707257,0.0002078909,0.0000309488],"domain_scores_gemma":[0.9998261,0.00007281134,0.00002362804,0.000030523,0.00003137459,0.00001561697],"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":[0.00004111465,0.00004225149,0.0001056584,0.0001911884,0.000008426012,0.0001151019,0.00001867083,0.00004180304,0.9878351,0.0007751797,0.001528464,0.009297009],"study_design_scores_gemma":[0.00004480876,0.0002703381,0.001831075,0.00003056298,0.00002545937,0.001365064,0.00001567201,0.002920096,0.9359172,0.0001966367,0.05735015,0.00003287857],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.131567,0.005923067,0.8362306,0.0007684377,0.001884675,0.002664482,0.003798105,0.006532132,0.01063144],"genre_scores_gemma":[0.1730379,0.004366665,0.7963138,0.0009879407,0.0002642245,0.003425497,0.00311047,0.0003074913,0.01818604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004568956,"threshold_uncertainty_score":0.01528472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01811089980407326,"score_gpt":0.3152060179930624,"score_spread":0.2970951181889891,"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."}}