{"id":"W4406005220","doi":"10.2460/ajvr.24.12.0382","title":"Research excellence across disciplines","year":2025,"lang":"en","type":"article","venue":"American Journal of Veterinary Research","topic":"Interdisciplinary Research and Collaboration","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Excellence; Engineering ethics; Data science; Political science; Computer science; Engineering; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05752424,0.0007343171,0.001492408,0.005438878,0.005355353,0.02668684,0.00254672,0.006445042,0.03651589],"category_scores_gemma":[0.06897444,0.0007796851,0.001079726,0.007316154,0.007008486,0.01659188,0.02290492,0.005305774,0.01135131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008184054,"about_ca_system_score_gemma":0.05408391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001790248,"about_ca_topic_score_gemma":0.003078563,"domain_scores_codex":[0.9319806,0.02496109,0.004199647,0.006971735,0.02490775,0.006979226],"domain_scores_gemma":[0.8760839,0.0169524,0.007154415,0.01555943,0.03140214,0.05284781],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001155052,0.000318424,0.007964529,0.0007567302,0.0001615564,0.0002147972,0.003372489,0.0004803519,0.001621135,0.5108424,0.1561553,0.3179968],"study_design_scores_gemma":[0.00004580489,0.0002151209,0.01335042,0.0008847183,0.00004959818,0.0003915496,0.006289789,0.0004965381,0.0009424709,0.1849236,0.7923667,0.00004354889],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02099938,0.02305766,0.01772795,0.2778814,0.0118677,0.0003322474,0.0003502471,0.0003317683,0.6474518],"genre_scores_gemma":[0.5934249,0.03574289,0.04007853,0.06727169,0.01350078,0.0006098428,0.001264575,0.0004064671,0.2477003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9424757,"threshold_uncertainty_score":0.3042209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4115852346523675,"score_gpt":0.65676808103864,"score_spread":0.2451828463862726,"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."}}