{"id":"W3090387320","doi":"10.1016/j.nmd.2020.08.217","title":"DMD – ANIMAL MODELS & PRECLINICAL TREATMENT","year":2020,"lang":"en","type":"article","venue":"Neuromuscular Disorders","topic":"Animal testing and alternatives","field":"Veterinary","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"AGADA Biosciences","funders":"","keywords":"Normative; Medicine; Consistency (knowledge bases); Regression; Forelimb; mdx mouse; Linear regression; Grip strength; Preclinical research; Benchmark (surveying); Body weight; Internal medicine; Duchenne muscular dystrophy; Physiology; Dystrophin; Statistics; Computer science; Medical physics; Mathematics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005884604,0.0002413605,0.0002516499,0.00002684916,0.0001086479,0.00004042112,0.0002293879,0.00006081143,0.000172379],"category_scores_gemma":[0.0001672849,0.0002116663,0.0002580652,0.0001310801,0.00008281397,0.0001462239,0.00009420493,0.0001733028,0.0003942654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000179255,"about_ca_system_score_gemma":0.00002666007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007527076,"about_ca_topic_score_gemma":0.00001399258,"domain_scores_codex":[0.9985036,0.0001578009,0.0002521855,0.0005719145,0.0002193829,0.0002951322],"domain_scores_gemma":[0.9993104,0.000131709,0.00007233734,0.0002692109,0.00002149388,0.0001948405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.02076911,0.01121408,0.1362141,0.0009067561,0.002997273,0.002528246,0.03579335,0.01911255,0.2527243,0.02040048,0.01450817,0.4828316],"study_design_scores_gemma":[0.01532838,0.0971582,0.1160522,0.0001914931,0.0007994641,0.000235898,0.001335346,0.2471362,0.000777069,0.01464314,0.5018486,0.004494021],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860249,0.0003065437,0.001543436,0.002420675,0.00008327499,0.0002566646,0.00001688124,0.0003915779,0.00895604],"genre_scores_gemma":[0.9975709,0.0001674144,0.001100769,0.0007062404,0.0001724677,0.00002849697,0.00001669935,0.00005354509,0.0001835014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4873405,"threshold_uncertainty_score":0.8631501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3626376224639702,"score_gpt":0.4209730568934479,"score_spread":0.05833543442947764,"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."}}