{"id":"W1978993187","doi":"10.1080/10888700801925513","title":"Caring During Crisis: Animal Welfare During Pandemics and Natural Disasters","year":2008,"lang":"en","type":"article","venue":"Journal of Applied Animal Welfare Science","topic":"Human-Animal Interaction Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"World Health Organization","keywords":"Animal welfare; Natural disaster; Government (linguistics); Pandemic; Public relations; Political science; Welfare; Economic growth; Coronavirus disease 2019 (COVID-19); Medicine; Geography; Ecology; Law; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002477058,0.0002268866,0.0002800687,0.0001811578,0.001137217,0.00008748703,0.0003864227,0.00007519651,0.000009496057],"category_scores_gemma":[0.00007085763,0.000196842,0.0001069415,0.0002323625,0.0004759696,0.00006224878,0.0004180352,0.0003438135,0.000001805325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010652,"about_ca_system_score_gemma":0.00006526306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001036667,"about_ca_topic_score_gemma":0.00001415925,"domain_scores_codex":[0.9982243,0.00001452327,0.0004529602,0.0004221106,0.0004693608,0.0004167697],"domain_scores_gemma":[0.9990298,0.000006715023,0.0003401086,0.0001713945,0.0002681965,0.0001838276],"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":[0.0008245961,0.00002336941,0.003278207,0.000027186,0.00004815983,0.00005223722,0.0007047756,0.00005114465,0.9946596,0.0002262928,0.00004606382,0.0000583731],"study_design_scores_gemma":[0.00120508,0.0005469734,0.5351949,0.00004214928,0.00004231279,0.002468933,0.01037841,0.00004074827,0.4468147,0.000006964437,0.002790997,0.0004679082],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979309,0.0004526232,0.000004962997,0.0006526255,0.0001814676,0.00008207681,0.000004674759,0.00001416234,0.0006765481],"genre_scores_gemma":[0.9989836,0.0001793497,0.0003859227,0.00006993656,0.0003185507,0.000003499756,9.640358e-7,0.00001997426,0.00003816125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5478449,"threshold_uncertainty_score":0.8746669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087282547540716,"score_gpt":0.2816875610953886,"score_spread":0.2708147356199814,"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."}}