{"id":"W4366091138","doi":"10.1080/21550085.2023.2200728","title":"Wild Animal Ethics: A Freedom-Based Approach","year":2023,"lang":"en","type":"article","venue":"Ethics Policy & Environment","topic":"Environmental Philosophy and Ethics","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Agència de Gestió d'Ajuts Universitaris i de Recerca; Fundação para a Ciência e a Tecnologia; Université de Montréal","keywords":"Animal ethics; Order (exchange); Freedom of choice; Animal rights; Control (management); Environmental ethics; Psychological intervention; Law and economics; Political science; Law; Sociology; Psychology; Computer science; Philosophy; Economics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003662627,0.0005850713,0.0003996644,0.0001987579,0.0009944356,0.00007603664,0.0009132603,0.001224241,0.001733349],"category_scores_gemma":[0.0005724629,0.0005927644,0.0002812885,0.0007266647,0.00235916,0.0002844293,0.001073756,0.004463044,0.01363667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009002184,"about_ca_system_score_gemma":0.0001183525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001064952,"about_ca_topic_score_gemma":0.00003993597,"domain_scores_codex":[0.9941008,0.0006685078,0.000587111,0.001213752,0.002264344,0.001165503],"domain_scores_gemma":[0.9970067,0.001021942,0.0002016657,0.001255252,0.00000447898,0.0005099997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004068007,0.002478,0.02187353,0.0004208345,0.0002185282,0.0001883784,0.02934751,0.7896226,0.05558362,0.07699081,0.02013594,0.002733448],"study_design_scores_gemma":[0.005423931,0.00206111,0.1983245,0.0002312168,0.0002933434,0.00007199217,0.002174336,0.06298,0.01149995,0.1134014,0.5980766,0.005461616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3011742,0.0003528107,0.01324016,0.3879846,0.0009027326,0.003575147,0.0006756744,0.002338655,0.289756],"genre_scores_gemma":[0.9764751,0.0005077336,0.005841417,0.01414706,0.0005517803,0.0001923486,0.0001900575,0.0001413528,0.001953099],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7266426,"threshold_uncertainty_score":0.9996524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08031985442265568,"score_gpt":0.3132211534328555,"score_spread":0.2329012990101998,"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."}}