{"id":"W4412933000","doi":"10.21203/rs.3.rs-7216255/v1","title":"Quantitative dual-isotope preclinical SPECT/CT imaging and biodistribution of the mercury-197m/g theranostic pair with [197m/gHg]HgCl2 and a superior [197m/gHg]Hg-tetrathiol complex as a platform for radiopharmaceutical development","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Radiopharmaceutical Chemistry and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; TRIUMF","keywords":"Biodistribution; Spect imaging; Mercury (programming language); Greenhouse gas; Environmental science; Radiochemistry; Nuclear medicine; Medical physics; Medicine; Chemistry; Computer science; Geology","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":[0.0004980778,0.0004495382,0.0002736217,0.0003911869,0.0001934227,0.0004127249,0.0005305093,0.0006912127,0.001662992],"category_scores_gemma":[0.0002339776,0.0002730505,0.0002211423,0.0003404405,0.0004132419,0.0002957659,0.0002694129,0.0005096513,0.0004151343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006967793,"about_ca_system_score_gemma":0.000605608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002491216,"about_ca_topic_score_gemma":0.001751648,"domain_scores_codex":[0.9998571,0.00003517025,0.000005459983,0.00003325244,0.00002519473,0.00004386126],"domain_scores_gemma":[0.999941,0.00001481262,0.00001353244,0.000007929944,0.00001079211,0.00001180465],"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":[0.0005697593,0.00005983162,0.0001770552,0.00004259189,0.00001258646,0.0001098683,0.00002844302,0.0004449133,0.9953283,0.0004388529,0.0002067685,0.002580929],"study_design_scores_gemma":[0.00004397025,0.0003258389,0.0006512359,0.00000381777,0.00003362152,0.0001695478,0.00001498084,0.003130427,0.9938312,0.00005367721,0.001732749,0.000008899977],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729767,0.001987797,0.01720385,0.0002888809,0.00005889537,0.000139315,0.0004348752,0.0002391296,0.006670543],"genre_scores_gemma":[0.9666786,0.0008756493,0.02427347,0.0001302577,0.00002182705,0.0001156302,0.000583691,0.0001379086,0.007182932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002491216,"threshold_uncertainty_score":0.005563259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1866380532994121,"score_gpt":0.4895486645867949,"score_spread":0.3029106112873828,"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."}}