{"id":"W4412122910","doi":"10.21203/rs.3.rs-7015694/v1","title":"Revisiting Centiloids using AI","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Computer Science and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; Servier; Eisai; European Commission; GHR Foundation; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; University of California, San Diego; Biogen; BioClinica; Eli Lilly and Company; U.S. Department of Defense; Medical Research Council; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Mayo Foundation for Medical Education and Research; Synarc; University of Southern California; Bristol-Myers Squibb; European Federation of Pharmaceutical Industries and Associations; Medpace; Alzheimer's Association","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001102083,0.0007464748,0.0006264025,0.001606654,0.002043393,0.004213416,0.001635532,0.001072508,0.0278714],"category_scores_gemma":[0.007533956,0.0004467917,0.001017329,0.00123197,0.004974958,0.006425048,0.003264131,0.002803477,0.006711701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001966071,"about_ca_system_score_gemma":0.001220752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006347673,"about_ca_topic_score_gemma":0.005853339,"domain_scores_codex":[0.9990429,0.0002854984,0.00007130799,0.0002197038,0.0002866705,0.000093887],"domain_scores_gemma":[0.9975505,0.001022509,0.0001130629,0.000813533,0.0003836344,0.000116728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008886967,0.00001224802,0.0002956328,0.0002106376,0.00001523578,0.0001030662,0.0009443951,0.002985259,0.001358069,0.9139084,0.007458657,0.07261956],"study_design_scores_gemma":[0.00002847971,0.00004351119,0.0002663753,0.0002162142,0.00002956895,0.0001649485,0.0006061103,0.01868824,0.002764606,0.7135711,0.2635829,0.00003797699],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03884625,0.005276169,0.5062931,0.007780565,0.004082594,0.000124324,0.0004592055,0.003503723,0.4336341],"genre_scores_gemma":[0.6163312,0.003388807,0.2540744,0.001465725,0.001019878,0.0001701378,0.0007043311,0.002800926,0.1200447],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0278714,"threshold_uncertainty_score":0.09323913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09122415451743834,"score_gpt":0.4157811154004898,"score_spread":0.3245569608830514,"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."}}