{"id":"W4404027518","doi":"10.5539/jas.v16n12p53","title":"Associations Between Microsatellites Markers and Growth Traits in Goat","year":2024,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microsatellite; Biology; Evolutionary biology; Genetics; Computational biology; Gene; Allele","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004320942,0.0001411518,0.0001263887,0.0007947319,0.000158701,0.0002301641,0.0001353233,0.0001306482,0.001143628],"category_scores_gemma":[0.0005918875,0.0001112555,0.0002104444,0.0004240557,0.0001837702,0.00008969756,0.0001967823,0.0001352369,0.0001358125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001244903,"about_ca_system_score_gemma":0.000166275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001987786,"about_ca_topic_score_gemma":0.003862973,"domain_scores_codex":[0.9998242,0.00003992103,0.00001465691,0.00005647169,0.00004136284,0.00002337582],"domain_scores_gemma":[0.9995971,0.0001214048,0.0001259727,0.00002541187,0.00006141471,0.00006868661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004625386,0.00007916407,0.8415746,0.00007353698,0.0002353259,0.0007408758,0.0009258109,0.0005899285,0.1428753,0.0002503219,0.0001787952,0.01201377],"study_design_scores_gemma":[0.000006110029,0.0001229909,0.9968246,0.000008055176,0.00004621847,0.0002351893,0.0001293399,0.0005264648,0.001621141,0.00006378623,0.0004113076,0.0000047968],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994705,0.00008147145,0.0002011124,0.00001097824,0.000001615036,0.000001985846,0.00007401489,0.000003067744,0.0001552698],"genre_scores_gemma":[0.9985977,0.00006708999,0.000501752,0.000007544674,0.000003977299,0.000006778531,0.0003090189,0.000003544004,0.000502563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001987786,"threshold_uncertainty_score":0.003952503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008353329974202283,"score_gpt":0.2369050889530444,"score_spread":0.2285517589788421,"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."}}