{"id":"W4212766651","doi":"10.3390/pr10020388","title":"Imaging Method by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI-MS) for Tissue or Tumor: A Mini Review","year":2022,"lang":"en","type":"review","venue":"Processes","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"MALDI imaging; Mass spectrometry imaging; Mass spectrometry; Matrix-assisted laser desorption/ionization; Surface-enhanced laser desorption/ionization; Instrumentation (computer programming); Chemistry; Desorption; Biological tissue; Analytical Chemistry (journal); Chromatography; Protein mass spectrometry; Computer science; Biomedical engineering; Tandem mass spectrometry; Medicine; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005705635,0.0007513132,0.00188942,0.0003115065,0.0003734476,0.000179746,0.0009977254,0.0001923868,0.03188362],"category_scores_gemma":[0.001039129,0.0006446749,0.0003971373,0.003135468,0.00004120223,0.0001751771,0.0001830407,0.0005550775,0.00003829817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005011326,"about_ca_system_score_gemma":0.0006606402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001602702,"about_ca_topic_score_gemma":0.000003290528,"domain_scores_codex":[0.9965189,0.00009364163,0.00121677,0.001128164,0.000481492,0.0005609935],"domain_scores_gemma":[0.9965972,0.0008745549,0.001287435,0.0008424307,0.0002438637,0.000154565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001074792,0.0002112691,0.000002188526,0.5397623,0.0001274732,0.00001164909,0.000006334692,1.340711e-7,0.00020433,0.0002221718,0.04675202,0.4126894],"study_design_scores_gemma":[0.0001489528,0.00003046986,1.999278e-8,0.0128956,0.001548158,0.0002783459,0.0000197548,0.00001298377,0.001780208,0.0004144341,0.9821408,0.0007303007],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[6.675501e-8,0.9333039,0.05858391,0.0002473077,0.00004148381,0.001608401,0.001300112,0.0005968657,0.004317935],"genre_scores_gemma":[0.00000105293,0.8815831,0.097213,0.0001793594,0.0002073,0.008409149,0.003880946,0.0002138009,0.008312271],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9353887,"threshold_uncertainty_score":0.9996005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04144817284483965,"score_gpt":0.3862603438735615,"score_spread":0.3448121710287218,"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."}}