{"id":"W3197044754","doi":"10.1039/d1an00725d","title":"The liquid micro junction-surface sampling probe (LMJ-SSP); a versatile ambient mass spectrometry interface","year":2021,"lang":"en","type":"review","venue":"The Analyst","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mass spectrometry; Profiling (computer programming); Sampling (signal processing); Interface (matter); Nanotechnology; Chemistry; Analytical Chemistry (journal); Materials science; Computer science; Chromatography; Molecule","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":[0.0006475772,0.0009947167,0.0008251616,0.001679257,0.0002879564,0.001010872,0.001068157,0.00108042,0.002427621],"category_scores_gemma":[0.0004915489,0.0003843811,0.0004966134,0.001542916,0.0005164957,0.001646844,0.0008467056,0.001819999,0.003247923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005018677,"about_ca_system_score_gemma":0.0006942701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004227255,"about_ca_topic_score_gemma":0.0006659958,"domain_scores_codex":[0.9996907,0.00003287863,0.00002032804,0.00005844716,0.0001648486,0.00003282947],"domain_scores_gemma":[0.999846,0.00005981054,0.00002770148,0.000008522347,0.00004197668,0.00001608309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008246295,0.00009507163,0.0001825653,0.01327134,0.00006594576,0.0003648942,0.00007552122,0.0005518112,0.07970762,0.01639771,0.01737838,0.8718268],"study_design_scores_gemma":[0.0000105125,0.0001519343,0.0003599561,0.0005934896,0.00005259812,0.001024338,0.00003241069,0.0004279246,0.03587201,0.001707925,0.9597297,0.00003720788],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001827355,0.974622,0.01030934,0.0005346181,0.0007104763,0.00005442132,0.0001068506,0.0001743939,0.01166071],"genre_scores_gemma":[0.008471089,0.9733987,0.008954655,0.000541145,0.0003176707,0.00009682268,0.0001926666,0.00003080564,0.007996458],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002427621,"threshold_uncertainty_score":0.008121133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03819566596709854,"score_gpt":0.3301349747347662,"score_spread":0.2919393087676676,"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."}}