{"id":"W2093051327","doi":"10.1007/s13167-010-0019-0","title":"New animal models of progressive neurodegeneration: tools for identifying targets in predictive diagnostics and presymptomatic treatment","year":2010,"lang":"en","type":"article","venue":"The EPMA Journal","topic":"Neurological diseases and metabolism","field":"Neuroscience","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Prince Edward Island","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Neurodegeneration; Disease; Medicine; Intensive care medicine; Intervention (counseling); Psychological intervention; Animal model; Neuroscience; Pathology; Psychology; Psychiatry; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001226592,0.0001071835,0.0001604249,0.00004148664,0.0001557087,0.0001418687,0.0001639718,0.00003408524,0.00002341453],"category_scores_gemma":[0.0009940235,0.00006223876,0.00006395698,0.00007211779,0.00007743175,0.0003558848,0.00004382359,0.0001740531,6.397186e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006929244,"about_ca_system_score_gemma":0.00006878861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002481091,"about_ca_topic_score_gemma":0.000002664665,"domain_scores_codex":[0.9991093,0.0001102499,0.0002470427,0.0001697648,0.0001728065,0.0001908645],"domain_scores_gemma":[0.9988695,0.0006751508,0.0001742037,0.0001174222,0.00003867895,0.0001249931],"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":[0.001206835,0.0006975484,0.001264412,0.00005016106,0.00003531961,0.0001827529,0.002721343,0.004343215,0.8939986,0.03060073,0.0006775624,0.06422151],"study_design_scores_gemma":[0.007001044,0.004503077,0.1164889,0.0001172125,0.0003909224,0.0009679563,0.0001651734,0.1352931,0.5702102,0.163225,0.001150119,0.0004874382],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944129,0.0007277706,0.003252366,0.0005820837,0.0003307256,0.0005891483,0.00003232931,0.00001027454,0.00006240587],"genre_scores_gemma":[0.9981555,0.0005154075,0.0007604621,0.0001749758,0.0003118355,0.00004137805,6.143317e-7,0.000009573145,0.00003024609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3237885,"threshold_uncertainty_score":0.2538023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07536354864073715,"score_gpt":0.3180265740089024,"score_spread":0.2426630253681653,"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."}}