{"id":"W4210978025","doi":"10.1101/2022.02.09.479610","title":"Sensitive Spatiotemporal Tracking of Spontaneous Metastasis in Deep Tissues via a Genetically-Encoded Magnetic Resonance Imaging Reporter","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cancer Research and Treatments","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lawson Health Research Institute; Ontario Institute for Cancer Research; Western University","funders":"","keywords":"Magnetic resonance imaging; Metastasis; Cancer cell; Context (archaeology); Cancer; In vivo; Cancer research; Bioluminescence imaging; Lymph node; Reporter gene; Pathology; Biology; Medicine; Gene; Gene expression; Transfection; Radiology; Internal medicine","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":[0.0002847114,0.0002674657,0.0001832477,0.000155584,0.0001010646,0.0002749201,0.0002562738,0.0003224227,0.000321021],"category_scores_gemma":[0.000185021,0.0001631881,0.0001830284,0.0001197257,0.0002739744,0.0002132246,0.0002711551,0.0005269256,0.0001749267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003057503,"about_ca_system_score_gemma":0.0002342367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009810097,"about_ca_topic_score_gemma":0.0008133007,"domain_scores_codex":[0.9999063,0.00001334544,0.000004807226,0.00003011123,0.00002323409,0.00002221716],"domain_scores_gemma":[0.9998285,0.00003813386,0.0000697193,0.00001560242,0.00002347657,0.00002451839],"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":[0.000007071324,0.000002993153,0.00003772328,0.000004865128,7.735613e-7,0.000008169537,0.000004002384,0.00007559071,0.9996291,0.00004503292,0.000009196336,0.0001755846],"study_design_scores_gemma":[0.000006631896,0.00009206524,0.0006020935,0.000002607723,0.000005277313,0.00007180887,0.00001069952,0.004101102,0.9944266,0.00004071931,0.0006353537,0.000004997484],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.909894,0.000465678,0.08813011,0.0001398632,0.00002180757,0.00005002524,0.0002381058,0.0003065599,0.0007538082],"genre_scores_gemma":[0.9631888,0.0003948881,0.03427187,0.00005011584,0.000006670944,0.00007943492,0.0002232927,0.00005934717,0.001725604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009810097,"threshold_uncertainty_score":0.002218425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0107246407033207,"score_gpt":0.2507664770815961,"score_spread":0.2400418363782754,"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."}}