{"id":"W3118388099","doi":"10.1038/s41598-020-79637-9","title":"TEM, SEM, and STEM-based immuno-CLEM workflows offer complementary advantages","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Health and Medical Research Council; Natural Sciences and Engineering Research Council of Canada; State Government of Victoria; Monash University","keywords":"Biology; Stem cell; Progenitor cell; Regeneration (biology); Cell biology; Neural stem cell; Computational biology","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":[0.00330867,0.001030261,0.0005945422,0.001687809,0.0007607286,0.001680939,0.000989865,0.0009731965,0.003284697],"category_scores_gemma":[0.001976191,0.0006113852,0.0005109191,0.0007751351,0.0009501369,0.001353156,0.001553825,0.00163481,0.002675823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000501729,"about_ca_system_score_gemma":0.0007758604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004650184,"about_ca_topic_score_gemma":0.00174769,"domain_scores_codex":[0.9988912,0.0002690999,0.0001512727,0.0002395068,0.0003479609,0.0001010903],"domain_scores_gemma":[0.9971095,0.0007004355,0.0003416608,0.0009813132,0.0006881477,0.000179105],"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":[0.0001506951,0.00007608775,0.001714127,0.0008671609,0.00007503768,0.0002381397,0.0002523,0.0009275209,0.9469818,0.004695568,0.002140735,0.04188085],"study_design_scores_gemma":[0.00002440865,0.0001567543,0.006370505,0.0001277608,0.00007871457,0.002413048,0.00026449,0.007183291,0.9302306,0.00240652,0.05066539,0.00007853715],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09302413,0.007579762,0.8712373,0.001111334,0.0004802576,0.0006740091,0.002641846,0.006603278,0.01664808],"genre_scores_gemma":[0.09225731,0.004268275,0.8949953,0.0005171392,0.0001070183,0.0006168809,0.002357797,0.001059146,0.003821059],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00330867,"threshold_uncertainty_score":0.01749814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008560958660523149,"score_gpt":0.3009009711106854,"score_spread":0.2923400124501623,"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."}}