{"id":"W2942645824","doi":"10.3390/ani9050219","title":"Food Preferences in Dogs: Effect of Dietary Composition and Intrinsic Variables on Diet Selection","year":2019,"lang":"en","type":"article","venue":"Animals","topic":"Human-Animal Interaction Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidad de Chile","keywords":"Breed; Food preference; Animal science; Dry matter; Biology; Preference; Food intake; Food science; Mathematics; Endocrinology; Statistics","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":[0.0001161634,0.00009136889,0.0001563337,0.00004880912,0.0000236072,0.000009485017,0.00003835823,0.00006134305,0.00002288402],"category_scores_gemma":[0.00002511978,0.00007690064,0.00002741387,0.00005225049,0.00002569967,0.00000517369,0.00004362726,0.00005848641,0.000009578418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008279555,"about_ca_system_score_gemma":0.000006043053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004169152,"about_ca_topic_score_gemma":0.0000836373,"domain_scores_codex":[0.9994411,0.00008133526,0.00013344,0.0001948928,0.00005955474,0.0000896472],"domain_scores_gemma":[0.999768,0.0000526982,0.00006179494,0.00007066427,0.00003243378,0.000014474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001407459,0.00004281,0.1105601,0.00006712865,0.00006797889,2.285067e-7,0.00005174944,0.00001726418,0.887117,0.000100023,0.0001120554,0.0004562257],"study_design_scores_gemma":[0.0006829736,0.0207995,0.3350975,0.0001094691,0.00002362902,0.000004576174,0.00005567357,0.0000367948,0.6425065,0.00008143146,0.0004587901,0.0001431589],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975448,0.0003492889,0.000004233869,0.00001712482,0.00005357448,0.0001774247,0.000005891934,0.000006097595,0.001841575],"genre_scores_gemma":[0.9996944,0.0001258864,0.00003606867,0.00003399551,0.00004182654,0.00001581649,0.000015046,0.00000632774,0.00003059674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2446105,"threshold_uncertainty_score":0.3135917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01448538056573418,"score_gpt":0.301515514552502,"score_spread":0.2870301339867678,"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."}}