{"id":"W4389920834","doi":"10.32920/24625188.v1","title":"Carrageenan Brain Phantom for Use in MRI","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; Toronto Metropolitan University","funders":"","keywords":"Imaging phantom; Relaxometry; Carrageenan; Materials science; Biomedical engineering; White matter; Dielectric; Relaxation (psychology); Nuclear magnetic resonance; Agar gel; Magnetic resonance imaging; Nuclear medicine; Medicine; Radiology; Physics; Optoelectronics; Internal medicine; Spin echo; Biology","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":[0.0005523476,0.0009696379,0.0003337522,0.0007647127,0.0003949512,0.0004836056,0.0005389972,0.0009930605,0.005917714],"category_scores_gemma":[0.0007407206,0.0003624358,0.0003029301,0.0005513122,0.000347107,0.0005485142,0.0003875515,0.000750776,0.002366526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003285138,"about_ca_system_score_gemma":0.0005264688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006806685,"about_ca_topic_score_gemma":0.0009889638,"domain_scores_codex":[0.9997347,0.00004881945,0.00001846355,0.00007387542,0.00009547752,0.00002866386],"domain_scores_gemma":[0.9996654,0.00008479632,0.00007109655,0.00006606892,0.00006916479,0.00004350752],"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":[0.0001202807,0.00003782435,0.0000439901,0.00009360947,0.000006141322,0.000176389,0.00004060187,0.000316982,0.9915366,0.0009800305,0.0007462454,0.005901216],"study_design_scores_gemma":[0.00003379023,0.0004370291,0.000594394,0.00003778283,0.00002992011,0.001472655,0.00001973826,0.003097492,0.9593337,0.0006694274,0.03423098,0.00004301442],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2425287,0.01379434,0.6958004,0.001592202,0.0008816856,0.003051677,0.004174913,0.007679404,0.03049682],"genre_scores_gemma":[0.3013884,0.007230321,0.6530208,0.0006147106,0.0001237352,0.002009191,0.00456296,0.0007055711,0.03034428],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005917714,"threshold_uncertainty_score":0.01979679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08078080894189514,"score_gpt":0.4036652322945444,"score_spread":0.3228844233526492,"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."}}