{"id":"W4406569939","doi":"10.1016/j.heliyon.2025.e42111","title":"Label-free Aβ plaque detection in Alzheimer's disease brain tissue using infrared microscopy and neural networks","year":2025,"lang":"en","type":"article","venue":"Heliyon","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen; Alzheimer Nederland; Ontario Ministry of Research, Innovation and Science","keywords":"Brain tissue; Microscopy; Neuroscience; Medicine; Pathology; Biomedical engineering; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003043627,0.0001478353,0.0001520582,0.0002325965,0.0001140407,0.0001980964,0.0003945215,0.00006560145,0.000002488351],"category_scores_gemma":[0.0001548191,0.0001648372,0.00002482099,0.0006989804,0.00004542323,0.0004795109,0.0004880616,0.0001806472,0.000001315944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006702038,"about_ca_system_score_gemma":0.00009469965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005502643,"about_ca_topic_score_gemma":0.00008749982,"domain_scores_codex":[0.9986811,0.0002845892,0.0002342627,0.0004095557,0.0001436053,0.0002468566],"domain_scores_gemma":[0.9990242,0.0003797219,0.00005940165,0.0004033694,0.00004115116,0.00009213723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002608129,0.0001939168,0.006161086,0.0002239729,0.00006726146,0.0001357435,0.0005549672,0.5880079,0.0147154,0.009368737,0.0004405006,0.3798697],"study_design_scores_gemma":[0.0005901351,0.00002709967,0.02085505,0.0001453432,0.00001329105,0.000006523172,0.000006055418,0.9688798,0.003232418,0.005691833,0.0003922988,0.0001601964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2627399,0.005302285,0.72989,0.001103826,0.0005889734,0.0002258378,0.000004459247,0.00007597182,0.00006866077],"genre_scores_gemma":[0.922601,0.0001057587,0.07493923,0.002089184,0.0001285313,0.0000295917,0.00000763576,0.00001995678,0.0000790941],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6598611,"threshold_uncertainty_score":0.6721867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0220423669961378,"score_gpt":0.3325152273684682,"score_spread":0.3104728603723304,"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."}}