{"id":"W7130911154","doi":"","title":"The Impact of the 1938 Fascist Anti-Semitic Laws on Italian Universities: The Case of Veterinary Medicine","year":2025,"lang":"en","type":"article","venue":"Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna)","topic":"Historical Medical Research and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Legislation; Dismissal; Politics; Damages; Veterinary education; Quality (philosophy); Scientific society","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003282273,0.0002733315,0.0005022707,0.0002047249,0.0008977372,0.000009386128,0.0006166695,0.00007931555,0.00009687122],"category_scores_gemma":[0.0002243766,0.000126681,0.0003448375,0.0006506191,0.002268757,0.00005651734,0.0004982646,0.0003933451,0.00001836353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006154258,"about_ca_system_score_gemma":0.0005311815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008220715,"about_ca_topic_score_gemma":0.00008051927,"domain_scores_codex":[0.9979754,0.000325493,0.0003265848,0.0003425622,0.0005304302,0.000499544],"domain_scores_gemma":[0.9972667,0.001428309,0.0001612073,0.0007456284,0.0001983539,0.0001998426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.01325961,0.006065909,0.146171,0.001873433,0.01467207,0.04027725,0.01116435,0.0005448862,0.01269566,0.558885,0.1731783,0.02121257],"study_design_scores_gemma":[0.01696474,0.01250067,0.7670181,0.003370146,0.002936207,0.003050046,0.02533199,0.0009626987,0.001568998,0.002802597,0.1625792,0.0009145761],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8586215,0.0004634043,0.00005918429,0.006993466,0.0002836988,0.0005928697,0.0001569954,0.00002291977,0.132806],"genre_scores_gemma":[0.9565963,0.0002816012,0.0000181053,0.0001514197,0.00004501143,0.000006400533,0.0000186287,0.00001273233,0.04286983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6208472,"threshold_uncertainty_score":0.8359331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02324050828657227,"score_gpt":0.3035676751598573,"score_spread":0.280327166873285,"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."}}