{"id":"W4283170071","doi":"10.1101/2022.06.19.496699","title":"A Multifunctional Anchor for Multimodal Expansion Microscopy","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Cancer Research UK; National Institutes of Health; Open Philanthropy Project; Howard Hughes Medical Institute","keywords":"RNA; Resolution (logic); Visualization; Microscopy; Computer science; Computational biology; Nanotechnology; Chemistry; Materials science; Physics; Biology; Artificial intelligence; Optics; Biochemistry","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":[0.0004042685,0.0005445986,0.0002310791,0.0003216499,0.0002766594,0.0003325133,0.0003850963,0.0005248699,0.002813965],"category_scores_gemma":[0.0003641665,0.0002382873,0.0001724551,0.0002230966,0.0002856228,0.0005192875,0.0009359586,0.0006692672,0.0008799776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003345065,"about_ca_system_score_gemma":0.0001534026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001761986,"about_ca_topic_score_gemma":0.0002226487,"domain_scores_codex":[0.9997923,0.00003467799,0.00001447003,0.00006835516,0.00004927148,0.00004106176],"domain_scores_gemma":[0.9997763,0.00005850376,0.00005438333,0.00004707652,0.00003194986,0.00003186535],"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":[0.0000212327,0.000008487221,0.00004941381,0.00003497046,0.0000020824,0.00003890355,0.00001675508,0.0001011044,0.9955883,0.0009429078,0.0001844322,0.00301128],"study_design_scores_gemma":[0.000006498,0.0000452355,0.0003797101,0.000005026971,0.000004959809,0.0001530732,0.00001014524,0.001644061,0.9904354,0.0001557738,0.007152349,0.00000775791],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6961575,0.001929514,0.2891618,0.0004820977,0.0002525892,0.0001805164,0.0005561231,0.001653577,0.009626299],"genre_scores_gemma":[0.8906952,0.0007162053,0.09774074,0.0001359121,0.00005093306,0.0002278038,0.000439353,0.0001596104,0.009834192],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002813965,"threshold_uncertainty_score":0.00941366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01199103633341531,"score_gpt":0.2633481242054523,"score_spread":0.251357087872037,"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."}}