{"id":"W2157129627","doi":"10.1002/sia.5596","title":"Detection of immunolabels with multi‐isotope imaging mass spectrometry","year":2014,"lang":"en","type":"article","venue":"Surface and Interface Analysis","topic":"Retinal Development and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"IONICS Mass Spectrometry (Canada)","funders":"National Institute on Aging; National Institutes of Health; Human Frontier Science Program; National Center for Research Resources; Massachusetts Eye and Ear; National Institute of Biomedical Imaging and Bioengineering; Ellison Medical Foundation","keywords":"Synaptophysin; Immunogold labelling; Synaptic vesicle; Chemistry; Mass spectrometry; Antibody; Retina; Isotope; Biophysics; Immunohistochemistry; Biochemistry; Biology; Chromatography; Vesicle; Neuroscience; Physics","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":[0.00118825,0.0009386466,0.0006089743,0.001461903,0.0005257617,0.0006862826,0.001228025,0.0009084278,0.001705924],"category_scores_gemma":[0.0008249654,0.0005961077,0.0005408855,0.0006129742,0.000676901,0.0009310832,0.0008384427,0.001256107,0.001212746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005856109,"about_ca_system_score_gemma":0.0003229179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004148914,"about_ca_topic_score_gemma":0.0008944549,"domain_scores_codex":[0.9992718,0.000117294,0.00004933355,0.0002287423,0.0002169716,0.0001159069],"domain_scores_gemma":[0.9994153,0.0001472781,0.0000990169,0.00009907934,0.0001683188,0.00007104447],"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":[0.00002525314,0.00001441299,0.0001568972,0.00004371595,0.00000738457,0.00003281031,0.00001329145,0.00005140697,0.9960696,0.0005046635,0.00008360718,0.002996975],"study_design_scores_gemma":[0.000007589414,0.00006827959,0.001059269,0.000007274409,0.00001465023,0.0002358115,0.00001555041,0.003506004,0.9918482,0.0002611761,0.002963661,0.00001242259],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2778496,0.003566359,0.7082261,0.0004483594,0.0002482791,0.0002215592,0.0004523321,0.002215061,0.006772324],"genre_scores_gemma":[0.3322259,0.002501054,0.65679,0.0003447521,0.0001020429,0.0004949134,0.0007961385,0.0003656201,0.006379606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001705924,"threshold_uncertainty_score":0.006284118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003603957134155701,"score_gpt":0.2218980259236785,"score_spread":0.2182940687895228,"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."}}