{"id":"W4320154570","doi":"10.52269/22266070_2022_4_193","title":"USING CANADIAN VYTELLE (GROWSAFE) TECHNOLOGY FOR EVALUATION QAZAQ AQBAS BREED","year":2022,"lang":"ru","type":"article","venue":"3i intellect idea innovation - интеллект идея инновация","topic":"Engineering and Material Science Research","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Breed; Animal science; Biology","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01040801,0.0005846361,0.0006651178,0.004127847,0.002849177,0.0005668725,0.001551296,0.0004391646,0.01446673],"category_scores_gemma":[0.004163945,0.000670881,0.0001471485,0.01020916,0.000420274,0.0005754619,0.0006336619,0.0007968607,0.0002905479],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004016303,"about_ca_system_score_gemma":0.004472839,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04018068,"about_ca_topic_score_gemma":0.003870449,"domain_scores_codex":[0.9927662,0.0005255037,0.00152694,0.001325572,0.001848321,0.002007449],"domain_scores_gemma":[0.9956781,0.0003490138,0.0005475695,0.0009452992,0.002160787,0.0003192701],"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":[0.00027519,0.0002006529,0.0001744326,0.0002367356,0.00008679933,0.00001657932,0.001294523,0.04007065,0.8845786,0.0408347,0.01528029,0.01695085],"study_design_scores_gemma":[0.003097073,0.001754879,0.0003199592,0.0002585461,0.0002037461,0.000177303,0.003497694,0.3208428,0.3895859,0.01585332,0.2622721,0.002136712],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9327706,0.0007728881,0.03137309,0.007957377,0.01270938,0.005264185,0.0009312268,0.0005193163,0.007702009],"genre_scores_gemma":[0.9907008,0.00003401962,0.004202129,0.0005754626,0.0005810601,0.0008758507,0.0002972004,0.000131197,0.002602238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4949927,"threshold_uncertainty_score":0.9998071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1010034286261776,"score_gpt":0.3661141277012222,"score_spread":0.2651106990750446,"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."}}