{"id":"W4361825874","doi":"10.1158/0008-5472.22433346.v1","title":"Supplementary Data from A Genetically Encoded Magnetic Resonance Imaging Reporter Enables Sensitive Detection and Tracking of Spontaneous Metastases in Deep Tissues","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lawson Health Research Institute; Ontario Institute for Cancer Research; Western University","funders":"","keywords":"Magnetic resonance imaging; Genetically engineered; Tracking (education); Nuclear magnetic resonance; Gene; Radiology; Biology; Medicine; Genetics; Physics; Psychology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001375602,0.002338766,0.001708162,0.003240873,0.001382292,0.001759938,0.003146413,0.002092507,0.6876428],"category_scores_gemma":[0.006900766,0.001660673,0.001352048,0.004336294,0.000575198,0.001695888,0.001383389,0.003093348,0.2194717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001535552,"about_ca_system_score_gemma":0.002247227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006249252,"about_ca_topic_score_gemma":0.01122131,"domain_scores_codex":[0.9990664,0.00007113972,0.0001306632,0.0001551095,0.0004032876,0.0001733904],"domain_scores_gemma":[0.9943499,0.002753956,0.0003911169,0.0008302004,0.0009526045,0.0007223015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001187885,0.0005590811,0.001073077,0.00275294,0.0001817832,0.0004504009,0.0001060405,0.002192711,0.04400474,0.008441536,0.9101197,0.02893004],"study_design_scores_gemma":[0.001577667,0.000483371,0.01391622,0.0004366839,0.0001836253,0.001460568,0.0001137945,0.008331724,0.1004985,0.02054765,0.8521281,0.0003222012],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003039137,0.0003497573,0.01183468,0.0009637916,0.00174272,0.0001599363,0.9699924,0.002378084,0.009539372],"genre_scores_gemma":[0.01623425,0.0008632536,0.02298581,0.0005966962,0.0003759273,0.000778573,0.939229,0.002302236,0.01663433],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6876428,"threshold_uncertainty_score":0.4455396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02003152312453374,"score_gpt":0.2881390510943167,"score_spread":0.268107527969783,"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."}}