{"id":"W2938100350","doi":"10.1177/026119291304100311","title":"Balancing Reduction and Refinement","year":2013,"lang":"en","type":"article","venue":"Alternatives to Laboratory Animals","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Council on Animal Care","funders":"","keywords":"Reduction (mathematics); Variety (cybernetics); Distress; Welfare; Balance (ability); Computer science; Risk analysis (engineering); Psychology; Medicine; Economics; Artificial intelligence; Clinical psychology; Mathematics; Neuroscience","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":[0.0001296777,0.0001685296,0.0001852917,0.00007631665,0.0001680727,0.00006888821,0.00009789429,0.00003272331,0.0005440261],"category_scores_gemma":[0.00004501772,0.0001512538,0.00002476587,0.000156161,0.0000615117,0.0002806318,0.0001388923,0.00008843803,0.0004107529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004226452,"about_ca_system_score_gemma":0.00001108207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000135332,"about_ca_topic_score_gemma":0.000001849665,"domain_scores_codex":[0.9990053,0.00006813897,0.0002084922,0.0003351869,0.0001510343,0.0002318868],"domain_scores_gemma":[0.9994572,0.00002503482,0.00006604839,0.0001517168,0.0001847789,0.0001151837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001176754,0.00005503167,0.02204959,0.0000251787,0.00006637768,0.00003425298,0.002480682,7.212954e-7,0.9627857,0.004497958,0.003603496,0.004283402],"study_design_scores_gemma":[0.0002715129,0.001346864,0.9749481,0.00004406218,0.00002255463,0.00002174144,0.002022384,0.000006541024,0.009649677,0.0002899255,0.01106887,0.0003077397],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945933,0.0004296117,0.00003543126,0.0006614183,0.000157146,0.0003148547,0.00003060612,0.00009907487,0.003678587],"genre_scores_gemma":[0.9983202,0.00004623513,0.000878632,0.0002142183,0.0002016659,0.0001328894,0.000001879742,0.00002092381,0.0001833509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.953136,"threshold_uncertainty_score":0.6167952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.035218447487956,"score_gpt":0.3293548857968003,"score_spread":0.2941364383088443,"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."}}