{"id":"W2791748821","doi":"10.1093/jas/skx073","title":"Estimating optimal observational sampling frequency of behaviors for cattle fed high- and low-forage diets","year":2018,"lang":"en","type":"article","venue":"Journal of Animal Science","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Ruminating; Forage; Animal science; Crossbreed; Mathematics; Barn; Sampling (signal processing); Rumination; Grazing; Statistics; Biology; Agronomy","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":[],"consensus_categories":[],"category_scores_codex":[0.0007889995,0.0001221458,0.000256057,0.0001134573,0.0004758865,0.00005589599,0.0002889332,0.00003997672,0.00003307095],"category_scores_gemma":[0.000364953,0.00009903364,0.0000788813,0.0002513302,0.0006634049,0.0006466449,0.0001256557,0.000114705,0.000001519729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006121594,"about_ca_system_score_gemma":0.0001468117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000673085,"about_ca_topic_score_gemma":0.000003245971,"domain_scores_codex":[0.9985949,0.00001366253,0.0004931108,0.0001948934,0.0004294493,0.0002739277],"domain_scores_gemma":[0.9984554,0.00009531104,0.0004461326,0.00008475708,0.0008114431,0.0001069694],"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":[0.0003873488,0.00007168439,0.06943242,0.00002868068,0.000009350958,0.00001062966,0.0006260712,0.000009507909,0.927855,0.0008542273,0.00003756247,0.0006775839],"study_design_scores_gemma":[0.0003395953,0.005470239,0.9863557,0.000104458,0.00004672155,0.0001455647,0.0003414094,0.0004993771,0.006292854,0.0002713265,0.000006296011,0.0001264879],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957774,0.00006395533,0.003511122,0.0001580133,0.0002869596,0.0001063499,0.00003010078,0.000008870768,0.00005726736],"genre_scores_gemma":[0.8896857,0.00000234908,0.1100402,0.00001971636,0.0002359568,0.000002892111,7.690128e-7,0.000008693086,0.000003776986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9215621,"threshold_uncertainty_score":0.4038475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1289481699469718,"score_gpt":0.3967096533049866,"score_spread":0.2677614833580149,"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."}}